Add Endor object model figure source

Reviewed-on: #47

apps/docs/scripts/auth-cli.ts

@@ -182,10 +182,10 @@ async function main() {
   assert.equal(researchResponse.status, 200, "authenticated research API");
   assert.ok(researchResponse.headers.get("cache-control")?.includes("no-store"));
   const research = await researchResponse.json();
-  assert.equal(research.companies.length, 1051);
+  assert.equal(research.companies.length, 1312);
   assert.equal(research.categories.length, 11);
-  assert.equal(research.evidence.length, 2235);
-  assert.equal(research.observations.length, 314);
+  assert.equal(research.evidence.length, 5354);
+  assert.equal(research.observations.length, 495);
   assert.equal((await request("/api/research/ai-companies", { method: "POST", headers })).status, 405);
   const researchPage = await request("/docs/other-research/ai-company-research/overview", { headers });
   assert.equal(researchPage.status, 200);

apps/docs/src/components/AICompanyResearch.tsx

@@ -1,6 +1,9 @@
 import { useEffect, useMemo, useRef, useState } from "react";
 import { useRouter } from "next/router";
 import IncomeDistribution from "./IncomeDistribution";
+import ArrDisclosures from "./ArrDisclosures";
+import BusinessModelAssessment from "./BusinessModelAssessment";
+import ResearchCandidates from "./ResearchCandidates";
 import {
   categorySummary, evidenceUrl, technicalReviewLabels, reviewCompanyIds, type ResearchEvidence, type ResearchReview, type ResearchSnapshot,
 } from "@/lib/ai-research";
@@ -55,7 +58,7 @@ export default function AICompanyResearch() {
     : router.isReady && typeof linkedCompany === "string" && data?.companies.some((c) => c.id === linkedCompany)
       ? linkedCompany : null;
   function setSelected(id: string | null) { setSelection({ route: router.asPath, id }); }
-  const [tab, setTab] = useState<"companies" | "revenue" | "sources" | "reviews">("companies");
+  const [tab, setTab] = useState<"companies" | "candidates" | "revenue" | "models" | "sources" | "reviews">("companies");
   const companySection = useRef<HTMLElement>(null);
   const detailSection = useRef<HTMLElement>(null);
   useEffect(() => {
@@ -127,7 +130,7 @@ export default function AICompanyResearch() {
     <section ref={companySection} className="research-section" aria-labelledby="research-records-title">
       <h2 id="research-records-title">研究数据</h2>
       <div className="research-tabs" role="group" aria-label="研究数据视图">
-        {([['companies','公司与产品'],['revenue','收入观测'],['sources','原始证据'],['reviews','核查记录']] as const).map(([id,label]) =>
+        {([['companies','公司与产品'],['candidates','候选与缺项'],['revenue','收入观测'],['models','商业模式初评'],['sources','原始证据'],['reviews','核查记录']] as const).map(([id,label]) =>
           <button key={id} aria-pressed={tab === id} onClick={() => setTab(id)}>{label}</button>)}
       </div>
       {tab === "companies" && <>
@@ -152,8 +155,11 @@ export default function AICompanyResearch() {
         {!filtered.length && <p className="research-message">没有匹配公司，请调整筛选条件。</p>}
         {filtered.length > pageSize && <nav className="research-pagination" aria-label="公司数据分页"><button disabled={page === 0} onClick={() => setPage((n) => n - 1)}>上一页</button><span>{page + 1} / {Math.ceil(filtered.length / pageSize)}</span><button disabled={(page + 1) * pageSize >= filtered.length} onClick={() => setPage((n) => n + 1)}>下一页</button></nav>}
       </>}
+      {tab === "models" && <BusinessModelAssessment data={data} onSelect={setSelected} onChooseCategory={chooseCategory} />}
+      {tab === "candidates" && <ResearchCandidates data={data} onSelect={setSelected} onChooseCategory={chooseCategory} />}
       {tab === "revenue" && <>
         <IncomeDistribution data={data} onSelect={setSelected} />
+        <ArrDisclosures data={data} onSelect={setSelected} />
         <h3>企业披露与估算的历史里程碑</h3>
         <p className="research-notice">这一组包含 {disclosedCompanies} 家公司的披露或估算信号；企业披露含公司或交易当事方公开材料，披露主体与审计状态见证据。多为异时点历史里程碑，期间收入不直接年化，ARR 与年化收入口径仍待核对，暂不计算其同期领域均值。币种未确认的记录仅显示原值，不绘制美元长度条。上面的平台MRR统计与这一组分开。</p>
         <div className="research-revenue-chart" aria-label="不同时间的公开收入里程碑，线性长度，非同行排名">{observed.map((o) => <div key={o.id}>

apps/docs/src/components/ArrDisclosures.tsx

@@ -0,0 +1,69 @@
+import { useState } from "react";
+import { evidenceUrl, type ResearchSnapshot } from "@/lib/ai-research";
+import { arrDisclosureCoverage, arrDisclosures, arrFieldGaps, type ArrFieldGap } from "@/lib/research-statistics";
+
+const labels: Record<string, string> = {
+  signal: "企业或当事方披露", estimate: "第三方估算",
+  historical: "历史披露", "historical-estimate": "历史估算",
+};
+const gapLabels: Record<ArrFieldGap, string> = {
+  date: "缺有效财务截至日", currency: "USD 未确认（含其他币种）",
+  amount: "下界、近似或非精确金额", estimate: "第三方估算",
+};
+
+export default function ArrDisclosures({ data, onSelect }: { data: ResearchSnapshot; onSelect: (id: string) => void }) {
+  const [category, setCategory] = useState("");
+  const [year, setYear] = useState("");
+  const [gap, setGap] = useState<ArrFieldGap | "">("");
+  const claims = arrDisclosures(data, { category, foundedYear: year ? Number(year) : undefined });
+  const rows = claims.filter(({ observation }) => !gap || arrFieldGaps(observation, data.asOf).includes(gap));
+  const gapCounts = (Object.keys(gapLabels) as ArrFieldGap[]).map((id) => ({
+    id, count: claims.filter(({ observation }) => arrFieldGaps(observation, data.asOf).includes(id)).length,
+  }));
+  const completeFields = claims.filter(({ observation }) => !arrFieldGaps(observation, data.asOf).length).length;
+  const coverage = arrDisclosureCoverage(data, year ? Number(year) : undefined);
+  const companies = new Set(claims.map((row) => row.company.id));
+  const categories = new Map(data.categories.map((item) => [item.id, item.name]));
+  const evidence = new Map(data.evidence.map((item) => [item.id, item]));
+  return <section aria-label="ARR披露分类表">
+    <h3>2025—2026 年成立公司的 ARR 披露</h3>
+    <p className="research-notice">这是跨时点证据表，共 {companies.size} 家公司、{claims.length} 条记录；同一公司的历史里程碑逐条保留，不能相加或视为独立公司。ARR 标签沿用原始披露，未证明经常性收入定义或审计状态；不纳入 MRR 图表，不计算同期行业均值或造假概率。仅收录明确标注的 ARR；定义冲突、目标、承诺、客户和前雇主收入排除，缺失不作零。</p>
+    <div className="research-filters">
+      <label>业务分类<select value={category} onChange={(event) => setCategory(event.target.value)}><option value="">全部分类</option>{data.categories.map((item) => <option key={item.id} value={item.id}>{item.name}</option>)}</select></label>
+      <label>成立年份<select value={year} onChange={(event) => setYear(event.target.value)}><option value="">2025 与 2026</option><option value="2025">2025</option><option value="2026">2026</option></select></label>
+      <label>补证项目<select value={gap} onChange={(event) => setGap(event.target.value as ArrFieldGap | "")}><option value="">全部记录</option>{gapCounts.map((item) => <option key={item.id} value={item.id}>{gapLabels[item.id]}（{item.count} 条）</option>)}</select></label>
+    </div>
+    <div className="research-table-wrap"><table>
+      <caption>ARR 披露覆盖：按公司当前分类及所选成立年份、每家公司计一次。点击分类筛选下方证据表。</caption>
+      <thead><tr><th>业务分类</th><th>已采集公司</th><th>企业或当事方披露</th><th>仅第三方估算</th><th>缺少 ARR</th><th>披露覆盖率</th></tr></thead>
+      <tbody>{coverage.filter((item) => item.companies > 0).map((item) => <tr key={item.id}>
+        <td><button onClick={() => setCategory(item.id)} aria-pressed={category === item.id}>{item.name}</button></td>
+        <td>{item.companies}</td><td>{item.reported}</td><td>{item.estimatedOnly}</td><td>{item.missing}</td>
+        <td>{new Intl.NumberFormat("zh-CN", { style: "percent", maximumFractionDigits: 1 }).format(item.disclosed / item.companies)}</td>
+      </tr>)}</tbody>
+    </table></div>
+    <p className="research-muted">分母含仅有目录资料的公司，覆盖率反映本次采集深度，不代表行业披露率。分类及收费模式采用公司当前资料；公司转向或同时经营多个产品时，历史 ARR 未必属于当前业务，需打开公司核对产品、主体与期间，不能据当前分类重归历史收入。企业披露含历史里程碑，同一公司兼有披露和估算时归企业披露；缺少 ARR 的公司仍可能有其他收入。披露时点、币种与合同定义未对齐，不能将已披露少数公司的均值外推至整个分类，也不能由离散性判断财务造假。</p>
+    <aside className="research-notice" aria-label="ARR比较前的补证检查">
+      <strong>ARR 比较前的补证检查</strong>
+      <p>当前分类及成立年下有 {claims.length} 条披露，{completeFields} 条同时具有有效日期、明确 USD、精确金额且不是第三方估算。补证筛选后显示 {rows.length} 条。</p>
+      <div className="income-options">{gapCounts.map((item) => <button key={item.id} aria-pressed={gap === item.id} onClick={() => setGap(gap === item.id ? "" : item.id)}>{gapLabels[item.id]}：{item.count}</button>)}</div>
+      <p>各项可重叠，不能相加为独立公司数。日期必须是经营指标截至日，网页访问、发布或更新时间不能代替；其他币种保留原值，不擅自换算。基础字段齐全也不证明可比，还需对齐收入定义、业务期间、收费模式、主体与独立验证；这些缺项不作为造假判定。</p>
+    </aside>
+    <div className="research-table-wrap"><table>
+      <caption>金额保留原币种、下界和估算身份；日期栏保留业务截至日缺项</caption>
+      <thead><tr><th>公司 / 当前分类</th><th>当前收费与交付模式</th><th>原始 ARR 声明</th><th>时点</th><th>身份 / 限制</th><th>证据</th></tr></thead>
+      <tbody>{rows.map(({ company, observation: item }) => {
+        const source = evidence.get(item.evidence);
+        const url = source && evidenceUrl(source.url);
+        return <tr key={item.id}>
+          <td><button onClick={() => onSelect(company.id)}>{company.name}</button><small>{categories.get(company.cat)} · {company.year}</small></td>
+          <td>{company.businessModel ?? company.price}</td>
+          <td>{item.bound !== "=" && item.bound}{new Intl.NumberFormat("zh-CN", { maximumFractionDigits: 2 }).format(item.value)} {item.unit}<small>{item.kind}</small></td>
+          <td>{item.timing}</td><td>{labels[item.selection]}<small>{item.reason}</small><small>{arrFieldGaps(item, data.asOf).map((id) => gapLabels[id]).join("；") || "基础字段齐全；定义、期间与主体仍须核实"}</small></td>
+          <td>{url ? <a href={url} target="_blank" rel="noopener noreferrer">{item.evidence} ↗</a> : item.evidence}</td>
+        </tr>;
+      })}</tbody>
+    </table></div>
+    {!rows.length && <p>当前分类、成立年与补证筛选没有符合条件的已记录 ARR 声明；不代表这些公司收入为零。</p>}
+  </section>;
+}

apps/docs/src/components/BusinessModelAssessment.tsx

@@ -0,0 +1,32 @@
+import { businessModelReviewType, evidenceUrl, reviewCompanyIds, type ResearchSnapshot } from "@/lib/ai-research";
+
+export default function BusinessModelAssessment({ data, onSelect, onChooseCategory }: {
+  data: ResearchSnapshot; onSelect: (id: string) => void; onChooseCategory: (id: string) => void;
+}) {
+  const reviews = data.reviews.filter((review) => review.type === businessModelReviewType && review.scope === "companies");
+  const evidence = new Map(data.evidence.map((item) => [item.id, item]));
+  return <section aria-labelledby="research-models-title">
+    <h3 id="research-models-title">商业模式初评</h3>
+    <p>从已核个案提炼收费方式、成本约束与下一步验证条件。已知事实与研究判断分列；同一种收费方式可以跨业务分类，以下个案不能代表整个行业。</p>
+    <p className="research-muted">这是基于当前证据的初步评估，不是收入预测或盈利排名。判断能否用于我们的业务，还需用实际客户任务、付费留存与交付成本验证；ARR 或平台 MRR 单独不能证明利润。</p>
+    {reviews.length ? <div className="research-table-wrap"><table>
+      <caption>收费模式与业务分类、公司明细及原始证据相互关联</caption>
+      <thead><tr><th scope="col">模式 / 业务分类</th><th scope="col">已核事实</th><th scope="col">初步判断 / 验证条件</th><th scope="col">参考个案与证据</th></tr></thead>
+      <tbody>{reviews.map((review) => {
+        const companyIds = new Set(reviewCompanyIds(data, review));
+        const companies = data.companies.filter((company) => companyIds.has(company.id));
+        const categories = data.categories.filter((category) => companies.some((company) => company.cat === category.id));
+        return <tr key={review.id}>
+          <td><strong>{review.company}</strong><div>{categories.map((category) => <button key={category.id} onClick={() => onChooseCategory(category.id)}>{category.name}</button>)}</div></td>
+          <td>{review.summary}</td><td>{review.handling}</td>
+          <td><div>{companies.map((company) => <button key={company.id} className="research-company-name" onClick={() => onSelect(company.id)}>{company.name}</button>)}</div>
+            <div>{review.evidenceIds.map((id) => {
+              const item = evidence.get(id); const url = item && evidenceUrl(item.url);
+              return item && url ? <p key={id}><a href={url} target="_blank" rel="noopener noreferrer">{item.title} ↗</a></p> : null;
+            })}</div>
+          </td>
+        </tr>;
+      })}</tbody>
+    </table></div> : <p>当前数据版本尚未记录商业模式初评。</p>}
+  </section>;
+}

apps/docs/src/components/IncomeDistribution.tsx

@@ -1,6 +1,6 @@
 import { useMemo, useState } from "react";
 import type { ResearchSnapshot } from "@/lib/ai-research";
-import { groupIncome, platformIncomeSample } from "@/lib/research-statistics";
+import { compareIncomeGroups, groupIncome, platformIncomeSample } from "@/lib/research-statistics";
 
 const usd = (value: number | null) => value === null ? "—" : new Intl.NumberFormat("zh-CN", {
   style: "currency", currency: "USD", maximumFractionDigits: 0,
@@ -23,6 +23,7 @@ export default function IncomeDistribution({ data, onSelect }: {
   const categoryGroups = [...new Set(groups.map((group) => group.category))].map((category) => ({
     category, rows: groups.filter((group) => group.category === category),
   }));
+  const comparisons = compareIncomeGroups(groups);
   const categories = new Map(data.categories.map((category) => [category.id, category.name]));
   const metric = annualize ? "MRR×12参考年化" : "平台MRR";
   const values = sample.points.map((point) => point.value);
@@ -47,6 +48,20 @@ export default function IncomeDistribution({ data, onSelect }: {
     <p>{splitModels ? "分组：业务类别 × 支付平台 × 收费与交付模式。同一类别下的多行是不同统计组，各自计算均值和中位数。" : "分组：业务类别 × 支付平台。同一平台内的收费模式已合并，不同支付平台仍分别统计。"}</p>
     <p className="research-notice">资料截至 {data.asOf}，纳入 {sample.points.length} 个产品，另有 {sample.excluded.length} 个 MRR 观测未纳入。{annualize ? "乘12只改变显示单位，不证明全年收入、续约或ARR；CV与相对敏感性不变。" : "MRR不等于近30日收款；平台数据连接也不等于财务审计。"}{dateWindow === "all" && " 当前包含不同时间的历史观测，不能称为同期对照。"}</p>
     {sample.points.length ? <>
+      <aside aria-label="当前窗口样本解读" className="research-notice">
+        <strong>当前窗口的样本解读</strong>
+        {comparisons.length ? comparisons.map((comparison) => <div key={comparison.key}>
+          <p>{comparison.provider} · {comparison.model}（仅比较各组 n≥3）：
+            {comparison.leastDispersed.stats.cv === comparison.mostDispersed.stats.cv
+              ? <>各组 CV 相同（{comparison.leastDispersed.stats.cv?.toFixed(3)}），没有离散度高低差异。</>
+              : <>{categories.get(comparison.mostDispersed.category)}更离散（CV {comparison.mostDispersed.stats.cv?.toFixed(3)}），{categories.get(comparison.leastDispersed.category)}较集中（CV {comparison.leastDispersed.stats.cv?.toFixed(3)}）。</>}
+            {comparison.leastSensitive.stats.largestRemovalDrop === comparison.mostSensitive.stats.largestRemovalDrop
+              ? <>各组移除最大值后的均值下降幅度相同（{percent(comparison.leastSensitive.stats.largestRemovalDrop)}）。</>
+              : <>{categories.get(comparison.mostSensitive.category)}的均值更受最大值影响，移除后下降 {percent(comparison.mostSensitive.stats.largestRemovalDrop)}；{categories.get(comparison.leastSensitive.category)}下降 {percent(comparison.leastSensitive.stats.largestRemovalDrop)}。</>}
+          </p>
+        </div>) : <p>当前没有至少两个可对照的统计组。需要相同支付平台、明确的收费模式标签，且各组至少 3 个产品；可调整同步窗口或创立年，不能将单个产品或两点均值当作领域典型。</p>}
+        <p>这些是所选产品样本内的描述，较集中或较不敏感也不证明行业均值可靠。最后同步日并非统一财务结账日，产品年龄、主体独立性、成本和留存仍待核；参考年化也不是已披露 ARR。</p>
+      </aside>
       <figure>
         <div className="research-table-wrap"><svg className="income-distribution-chart" viewBox={`0 0 900 ${groups.length * 70 + 65}`} role="group" aria-label={`${metric}分布，${logScale ? "对数" : "线性"}横轴；圆点为产品，竖线为均值，菱形为中位数`}>
           {ticks.map((tick) => <g key={tick}><line x1={x(tick)} x2={x(tick)} y1={15} y2={groups.length * 70 + 10} stroke="#dfe6e0" /><text x={x(tick)} y={groups.length * 70 + 35} textAnchor="middle" fontSize="11" fill="#637066">{usd(tick)}</text></g>)}

apps/docs/src/components/ResearchCandidates.tsx

@@ -0,0 +1,75 @@
+import { useMemo, useState } from "react";
+import { evidenceUrl, type ResearchCandidateBatch, type ResearchSnapshot } from "@/lib/ai-research";
+
+type CandidateStatus = ResearchCandidateBatch["records"][number]["status"];
+const statusLabels: Record<CandidateStatus, string> = {
+  "pending-year": "成立年或主体待核", "pending-ai": "AI 主营待核", linked: "已关联公司",
+  "existing-outside-cohort": "已关联范围外对照", "outside-cohort": "范围外候选", promotion: "推广活动",
+};
+const pageSize = 20;
+const sourceNames: Record<string, string> = {
+  S01: "Y Combinator", S02: "TechCrunch AI", S04: "Product Hunt", S05: "Sacra",
+  S10: "机器之心", S11: "36氪", S13: "TrustMRR", S14: "a16z Speedrun",
+};
+const sourceLabel = (id: string) => `${id} · ${sourceNames[id] ?? "其他来源"}`;
+
+function SourceLink({ url, label }: { url: string | null; label: string }) {
+  const safe = url && evidenceUrl(url);
+  return safe ? <a href={safe} target="_blank" rel="noopener noreferrer">{label} ↗</a> : <span>{label}（链接未取得）</span>;
+}
+
+export default function ResearchCandidates({ data, onSelect, onChooseCategory }: {
+  data: ResearchSnapshot; onSelect: (id: string) => void; onChooseCategory: (id: string) => void;
+}) {
+  const [source, setSource] = useState("");
+  const [batchId, setBatchId] = useState("");
+  const [category, setCategory] = useState("");
+  const [status, setStatus] = useState<CandidateStatus | "pending" | "">("pending");
+  const [query, setQuery] = useState("");
+  const [page, setPage] = useState(0);
+  const all = useMemo(() => (data.candidateBatches ?? []).flatMap((batch) => batch.records.map((record) => ({ batch, record }))), [data.candidateBatches]);
+  const sources = [...new Set(all.map(({ batch }) => batch.sourceId))].sort();
+  const batches = (data.candidateBatches ?? []).filter((batch) => !source || batch.sourceId === source);
+  const matched = all.filter(({ batch, record }) => (!source || batch.sourceId === source)
+    && (!batchId || batch.id === batchId) && (!category || record.categoryId === category)
+    && `${record.name} ${record.id} ${record.note}`.toLocaleLowerCase().includes(query.trim().toLocaleLowerCase()));
+  const pending = (value: CandidateStatus) => value === "pending-year" || value === "pending-ai";
+  const rows = matched.filter(({ record }) => !status || (status === "pending" ? pending(record.status) : record.status === status));
+  const companies = new Map(data.companies.map((company) => [company.id, company]));
+  const evidence = new Map(data.evidence.map((item) => [item.id, item]));
+  const categories = new Map(data.categories.map((item) => [item.id, item.name]));
+  return <section aria-labelledby="research-candidates-title">
+    <h3 id="research-candidates-title">候选与缺项</h3>
+    <p>展示已登记的有限来源批次及后续核查。默认显示成立年、主体或 AI 主营待核的条目；待核不是确认排除，也不计入公司表。每行是一次发现位置，同一公司或产品可以重复出现。</p>
+    <p className="research-muted">候选初分类与公司表数量分开，来源批次不等全年或全站名单。原始发现范围及后续结论见每行说明；暂无收入资料不作零，推广活动也不算公司。</p>
+    <div className="research-filters">
+      <label className="research-query">搜索候选<input type="search" value={query} placeholder="名称、编号或核查说明" onChange={(event) => { setQuery(event.target.value); setPage(0); }} /></label>
+      <label>发现来源<select value={source} onChange={(event) => { setSource(event.target.value); setBatchId(""); setPage(0); }}><option value="">全部已登记来源</option>{sources.map((id) => <option key={id} value={id}>{sourceLabel(id)}</option>)}</select></label>
+      <label>发现批次<select value={batchId} onChange={(event) => { setBatchId(event.target.value); setPage(0); }}><option value="">全部批次</option>{batches.map((batch) => <option key={batch.id} value={batch.id}>{batch.id}</option>)}</select></label>
+      <label>候选初分类<select value={category} onChange={(event) => { setCategory(event.target.value); setPage(0); }}><option value="">全部分类</option>{data.categories.map((item) => <option key={item.id} value={item.id}>{item.name}</option>)}</select></label>
+      <label>核查状态<select value={status} onChange={(event) => { setStatus(event.target.value as typeof status); setPage(0); }}>
+        <option value="">全部状态（{matched.length}）</option><option value="pending">全部待核（{matched.filter(({ record }) => pending(record.status)).length}）</option>
+        {Object.entries(statusLabels).map(([id, label]) => <option key={id} value={id}>{label}（{matched.filter(({ record }) => record.status === id).length}）</option>)}
+      </select></label>
+    </div>
+    <p role="status">{rows.length} 个发现位置匹配；不是独立公司数。</p>
+    <div className="research-table-wrap"><table>
+      <caption>有限来源候选与处理记录；选择关联公司查看主数据，原始证据直接链接来源</caption>
+      <thead><tr><th scope="col">候选</th><th scope="col">初分类 / 状态</th><th scope="col">来源及范围</th><th scope="col">核查结论 / 缺项</th><th scope="col">关联公司 / 证据</th></tr></thead>
+      <tbody>{rows.slice(page * pageSize, (page + 1) * pageSize).map(({ batch, record }) => {
+        const company = record.companyId && companies.get(record.companyId);
+        return <tr key={record.id}>
+          <td><SourceLink url={record.url} label={record.name} /><small>{record.id}</small></td>
+          <td><button onClick={() => onChooseCategory(record.categoryId)} aria-label={`查看${categories.get(record.categoryId)}分类内的公司`}>{categories.get(record.categoryId)}</button><small>{statusLabels[record.status]}</small></td>
+          <td><SourceLink url={batch.url} label={sourceLabel(batch.sourceId)} /><small>{batch.id} · 读取 {batch.accessedAt}</small><details><summary>发现批次范围</summary><p>{batch.scope}</p><p>{batch.complete ? "该批次标记已完成；不代表来源全站覆盖。" : "该批次仍保留覆盖缺项。"}</p></details></td>
+          <td>{record.note}</td>
+          <td>{company ? <button className="research-company-name" onClick={() => onSelect(company.id)}>{company.name}</button> : <small>尚未关联公司主记录</small>}
+            {record.evidenceIds?.map((id) => { const item = evidence.get(id); return item ? <p key={id}><SourceLink url={item.url} label={id} /></p> : null; })}
+          </td>
+        </tr>;
+      })}</tbody>
+    </table></div>
+    {!rows.length && <p>当前筛选没有已登记的候选记录；不代表该来源或分类没有公司。</p>}
+    {rows.length > pageSize && <nav className="research-pagination" aria-label="候选与缺项分页"><button disabled={page === 0} onClick={() => setPage((value) => value - 1)}>上一页</button><span>{page + 1} / {Math.ceil(rows.length / pageSize)}</span><button disabled={(page + 1) * pageSize >= rows.length} onClick={() => setPage((value) => value + 1)}>下一页</button></nav>}
+  </section>;
+}

apps/docs/src/lib/ai-research.ts

@@ -1,4 +1,5 @@
 export type ResearchCategory = { id: string; name: string; description: string };
+export const businessModelReviewType = "商业模式初评";
 export const technicalReviewLabels = {
   unreviewed: "技术证据尚未专项评审",
   description: "已读技术自述",
@@ -48,7 +49,7 @@ export type ResearchCandidateBatch = {
   records: {
     id: string; name: string; url: string | null; categoryId: string;
     kind: "product" | "company" | "promotion"; profileStatus: "readable" | "unavailable" | "archive-only";
-    status: "pending-year" | "linked" | "existing-outside-cohort" | "outside-cohort" | "promotion";
+    status: "pending-year" | "pending-ai" | "linked" | "existing-outside-cohort" | "outside-cohort" | "promotion";
     companyId?: string; evidenceIds?: string[]; note: string;
   }[];
 };
@@ -125,13 +126,13 @@ export function validateResearch(snapshot: ResearchSnapshot) {
       if (!row.name.trim() || !row.note.trim() || !categories.has(row.categoryId) ||
           !["product", "company", "promotion"].includes(row.kind) ||
           !["readable", "unavailable", "archive-only"].includes(row.profileStatus) ||
-          !["pending-year", "linked", "existing-outside-cohort", "outside-cohort", "promotion"].includes(row.status) ||
+          !["pending-year", "pending-ai", "linked", "existing-outside-cohort", "outside-cohort", "promotion"].includes(row.status) ||
           (row.kind !== "promotion" && (!row.url || !evidenceUrl(row.url))) ||
           (row.url !== null && !evidenceUrl(row.url)) ||
           linked !== !!row.companyId || (row.companyId && !companies.has(row.companyId)) ||
           (row.kind === "promotion") !== (row.status === "promotion") ||
           (row.evidenceIds ?? []).some((id) => !evidence.has(id)) ||
-          (row.status === "outside-cohort" && !row.evidenceIds?.length))
+          (["outside-cohort", "pending-ai"].includes(row.status) && !row.evidenceIds?.length))
         throw new Error(`Invalid research candidate: ${row.id}`);
     }
   }

apps/docs/src/lib/research-statistics.ts

@@ -1,6 +1,50 @@
 import type { ResearchCompany, ResearchObservation, ResearchSnapshot } from "./ai-research";
 
 export type IncomePoint = { company: ResearchCompany; observation: ResearchObservation; value: number };
+
+/** An evidence ledger, never a comparable sample: retain historical claims and estimates separately. */
+export function arrDisclosures(snapshot: ResearchSnapshot, options: { category?: string; foundedYear?: number } = {}) {
+  const companies = new Map(snapshot.companies.map((company) => [company.id, company]));
+  return snapshot.observations.flatMap((observation) => {
+    const company = companies.get(observation.company);
+    if (!company || ![2025, 2026].includes(company.year ?? 0) || observation.metric !== "arr" ||
+        !["signal", "estimate", "historical", "historical-estimate"].includes(observation.selection) ||
+        !Number.isFinite(observation.value) || observation.value < 0 ||
+        (options.category && company.cat !== options.category) ||
+        (options.foundedYear && company.year !== options.foundedYear)) return [];
+    return [{ company, observation }];
+  });
+}
+
+/** Count companies once; missing ARR is a coverage gap, never zero revenue. */
+export function arrDisclosureCoverage(snapshot: ResearchSnapshot, foundedYear?: number) {
+  const rows = arrDisclosures(snapshot, { foundedYear });
+  return snapshot.categories.map((category) => {
+    const companies = snapshot.companies.filter((company) => company.cat === category.id &&
+      [2025, 2026].includes(company.year ?? 0) && (!foundedYear || company.year === foundedYear));
+    const claims = rows.filter((row) => row.company.cat === category.id);
+    const disclosed = new Set(claims.map((row) => row.company.id));
+    const reported = new Set(claims.filter((row) =>
+      ["signal", "historical"].includes(row.observation.selection)).map((row) => row.company.id));
+    return { id: category.id, name: category.name, companies: companies.length,
+      disclosed: disclosed.size, reported: reported.size, estimatedOnly: disclosed.size - reported.size,
+      missing: companies.length - disclosed.size, records: claims.length };
+  });
+}
+
+export type ArrFieldGap = "date" | "currency" | "amount" | "estimate";
+
+/** Prerequisites for inspecting exact, dated USD disclosures; never a comparability or audit verdict. */
+export function arrFieldGaps(observation: ResearchObservation, asOf: string): ArrFieldGap[] {
+  const gaps: ArrFieldGap[] = [];
+  const day = calendarDay(observation.observedAt);
+  const end = calendarDay(asOf);
+  if (day === null || end === null || day > end) gaps.push("date");
+  if (observation.unit !== "USD") gaps.push("currency");
+  if (observation.bound !== "=" || !Number.isFinite(observation.value) || observation.value < 0) gaps.push("amount");
+  if (["estimate", "historical-estimate"].includes(observation.selection)) gaps.push("estimate");
+  return gaps;
+}
 export type IncomeStats = {
   n: number; mean: number; median: number; min: number; max: number;
   sampleDeviation: number | null; cv: number | null; meanMedianRatio: number | null;
@@ -80,3 +124,24 @@ export function groupIncome(points: IncomePoint[], splitModels = true) {
   }
   return [...groups.entries()].map(([key, group]) => ({ key, ...group, stats: describeIncome(group.points.map((point) => point.value))! }));
 }
+
+/** Compare descriptive statistics only within the same provider and delivery model. */
+export function compareIncomeGroups(groups: ReturnType<typeof groupIncome>) {
+  const buckets = new Map<string, typeof groups>();
+  for (const group of groups) {
+    if (group.stats.n < 3 || group.stats.cv === null || group.stats.largestRemovalDrop === null ||
+        group.model === "全部收费模式" || group.model === "收费模式未核验") continue;
+    const key = JSON.stringify([group.provider, group.model]);
+    const bucket = buckets.get(key) ?? [];
+    bucket.push(group);
+    buckets.set(key, bucket);
+  }
+  return [...buckets.entries()].flatMap(([key, rows]) => {
+    if (rows.length < 2) return [];
+    const byCV = [...rows].sort((a, b) => a.stats.cv! - b.stats.cv! || a.key.localeCompare(b.key));
+    const bySensitivity = [...rows].sort((a, b) => a.stats.largestRemovalDrop! - b.stats.largestRemovalDrop! || a.key.localeCompare(b.key));
+    return [{ key, provider: rows[0].provider, model: rows[0].model,
+      leastDispersed: byCV[0], mostDispersed: byCV[byCV.length - 1],
+      leastSensitive: bySensitivity[0], mostSensitive: bySensitivity[bySensitivity.length - 1] }];
+  });
+}

apps/docs/tests/research.test.ts

@@ -8,10 +8,111 @@ import coverageAudit from "../../../content/research/ai-companies.coverage.json"
 import incomeReference from "../../../content/research/ai-income-analysis.json";
 import { readResearchSnapshot } from "../src/lib/ai-research-store";
 import { openSiteDatabase } from "../src/lib/site-database";
-import { categorySummary, evidenceUrl, reviewCompanyIds, validateResearch, type ResearchSnapshot } from "../src/lib/ai-research";
+import { businessModelReviewType, categorySummary, evidenceUrl, reviewCompanyIds, validateResearch, type ResearchSnapshot } from "../src/lib/ai-research";
 import { consumeCode, initializeStore } from "../src/lib/auth-store";
 import { newAuthConfig } from "../src/lib/auth";
-import { describeIncome, groupIncome, platformIncomeSample } from "../src/lib/research-statistics";
+import { arrDisclosureCoverage, arrDisclosures, arrFieldGaps, compareIncomeGroups, describeIncome, groupIncome, platformIncomeSample } from "../src/lib/research-statistics";
+
+test("ARR field checks distinguish missing dates, other currencies, bounds and estimates", () => {
+  const observation = { ...seed.observations[0], metric: "arr", unit: "USD", value: 100,
+    bound: "=", selection: "signal", observedAt: "2026-10-30" } as ResearchSnapshot["observations"][number];
+  assert.deepEqual(arrFieldGaps(observation, "2026-10-31"), []);
+  for (const observedAt of [undefined, "2026-02-30", "2026-11-01"])
+    assert.deepEqual(arrFieldGaps({ ...observation, observedAt }, "2026-10-31"), ["date"]);
+  assert.deepEqual(arrFieldGaps({ ...observation, unit: "EUR" }, "2026-10-31"), ["currency"],
+    "known foreign currencies stay distinct without an invented USD conversion");
+  assert.deepEqual(arrFieldGaps({ ...observation, unit: "原文$，币种待核", bound: ">",
+    selection: "historical-estimate", observedAt: undefined }, "2026-10-31"), ["date", "currency", "amount", "estimate"]);
+  assert.deepEqual(arrFieldGaps({ ...observation, value: Number.NaN }, "2026-10-31"), ["amount"]);
+  assert.deepEqual(arrFieldGaps({ ...observation, value: -1 }, "2026-10-31"), ["amount"]);
+  assert.deepEqual(arrFieldGaps({ ...observation, value: 0 }, "2026-10-31"), [], "disclosed zero is a valid amount");
+  const rows = arrDisclosures(seed as ResearchSnapshot);
+  assert.ok(rows.length > 0);
+  assert.ok(rows.every(({ observation: claim }) => arrFieldGaps(claim, seed.asOf).length > 0),
+    "the current ledger cannot be described as a complete dated exact USD sample");
+});
+
+test("income interpretations compare sufficient samples within a provider and known billing model", () => {
+  const snapshot = structuredClone(seed) as ResearchSnapshot;
+  const makePoints = (cat: string, values: number[], provider = "Stripe", model = "软件订阅") => values.map((value, index) => ({
+    company: { ...snapshot.companies[0], id: `${cat}-${provider}-${model}-${index}`, cat, businessModel: model },
+    observation: { ...snapshot.observations[0], provider }, value,
+  }));
+  const points = [
+    ...makePoints("C04", [100, 100, 100]),
+    ...makePoints("C06", [10, 10, 1000]),
+    ...makePoints("C08", [1, 10000]),
+    ...makePoints("C09", [1, 10, 10000], "RevenueCat"),
+    ...makePoints("C10", [1, 10, 10000], "Stripe", "硬件服务"),
+    ...makePoints("C07", [0, 0, 0]),
+    ...makePoints("C01", [1, 10, 100], "Stripe", "收费模式未核验"),
+  ];
+  const comparisons = compareIncomeGroups(groupIncome(points));
+  assert.equal(comparisons.length, 1);
+  assert.equal(comparisons[0].leastDispersed.category, "C04");
+  assert.equal(comparisons[0].mostDispersed.category, "C06");
+  assert.equal(comparisons[0].leastSensitive.category, "C04");
+  assert.equal(comparisons[0].mostSensitive.category, "C06");
+  assert.deepEqual(compareIncomeGroups(groupIncome(points, false)), [], "merged billing models are not comparable here");
+  const annualized = compareIncomeGroups(groupIncome(points.map((point) => ({ ...point, value: point.value * 12 }))));
+  assert.equal(annualized[0].mostSensitive.category, comparisons[0].mostSensitive.category);
+  assert.ok(Math.abs(annualized[0].mostDispersed.stats.cv! - comparisons[0].mostDispersed.stats.cv!) < 1e-12);
+});
+
+test("ARR coverage counts companies once and separates missing disclosures from zero income", () => {
+  const snapshot = structuredClone(seed) as ResearchSnapshot;
+  snapshot.categories = [{ id: "C07", name: "行业应用", description: "" }];
+  const template = snapshot.companies[0];
+  snapshot.companies = [
+    { ...template, id: "reported", cat: "C07", year: 2025 },
+    { ...template, id: "estimated", cat: "C07", year: 2026 },
+    { ...template, id: "missing", cat: "C07", year: 2025 },
+    { ...template, id: "old", cat: "C07", year: 2024 },
+    { ...template, id: "undated", cat: "C07", year: null },
+  ];
+  const observation = snapshot.observations[0];
+  snapshot.observations = [
+    { ...observation, id: "zero", company: "reported", metric: "arr", selection: "signal", value: 0 },
+    { ...observation, id: "past", company: "reported", metric: "arr", selection: "historical", value: 10 },
+    { ...observation, id: "estimate", company: "reported", metric: "arr", selection: "estimate", value: 20 },
+    { ...observation, id: "only-estimate", company: "estimated", metric: "arr", selection: "historical-estimate", value: 30 },
+    { ...observation, id: "goal", company: "missing", metric: "arr", selection: "excluded", value: 40 },
+    { ...observation, id: "mrr", company: "missing", metric: "mrr", selection: "platform", value: 50 },
+    { ...observation, id: "old-arr", company: "old", metric: "arr", selection: "signal", value: 60 },
+  ];
+  assert.deepEqual(arrDisclosureCoverage(snapshot), [{ id: "C07", name: "行业应用",
+    companies: 3, disclosed: 2, reported: 1, estimatedOnly: 1, missing: 1, records: 4 }]);
+  assert.deepEqual(arrDisclosureCoverage(snapshot, 2025), [{ id: "C07", name: "行业应用",
+    companies: 2, disclosed: 1, reported: 1, estimatedOnly: 0, missing: 1, records: 3 }]);
+});
+
+test("ARR ledger preserves historical estimates without promoting targets, run rates or outside-cohort claims", () => {
+  const snapshot = structuredClone(seed) as ResearchSnapshot;
+  const rows = arrDisclosures(snapshot);
+  const ids = new Set(rows.map((row) => row.observation.id));
+  for (const id of ["O064", "O065", "O066", "O069", "O070", "O071", "O046"])
+    assert.ok(ids.has(id), `${id}: historical claims, estimates and unknown currencies remain visible`);
+  for (const id of ["O050", "O052", "O053", "O055", "SR-O-AI067-runrate", "ROCKET-O-arr", "AQ-O-RUNRATE",
+    "SRLEARN1-O-CLAIR-D2C", "SRLEARN1-O-CLAIR-B2B"])
+    assert.ok(!ids.has(id), `${id}: excluded or ambiguous records cannot enter the ARR ledger`);
+  assert.equal(rows.find((row) => row.observation.id === "O066")?.observation.selection, "historical-estimate");
+  assert.equal(rows.find((row) => row.observation.id === "O046")?.observation.unit, "原文$，币种待核");
+  for (const id of ["O045", "O047"])
+    assert.equal(rows.find((row) => row.observation.id === id)?.observation.unit, "原文$，币种待核",
+      "current subscription prices cannot establish the currency of a historical ARR claim");
+  const category = snapshot.companies.find((company) => company.id === "AI055")!.cat;
+  const filtered = arrDisclosures(snapshot, { category, foundedYear: 2025 });
+  assert.ok(filtered.length > 0);
+  assert.ok(filtered.every((row) => row.company.cat === category && row.company.year === 2025));
+  // A future mistakenly typed target still must not enter the ledger.
+  const target = snapshot.observations.find((item) => item.id === "O052")!;
+  target.metric = "arr";
+  target.company = "AI055";
+  assert.ok(!arrDisclosures(snapshot).some((row) => row.observation.id === target.id));
+  const claim = snapshot.observations.find((item) => item.id === "O065")!;
+  claim.value = Number.NaN;
+  assert.ok(!arrDisclosures(snapshot).some((row) => row.observation.id === claim.id));
+});
 
 test("research revisions share the authentication database and preserve replay limits", () => {
   const dir = mkdtempSync(join(tmpdir(), "site-research-"));
@@ -23,9 +124,14 @@ test("research revisions share the authentication database and preserve replay l
     for (let i = 0; i < 20; i++) consumeCode(config, "invalid");
     assert.equal(consumeCode(config, "invalid"), "limited");
     const initial = readResearchSnapshot();
-    assert.equal(initial.companies.length, 1051);
-    assert.equal(initial.evidence.length, 2235);
-    assert.equal(initial.observations.length, 314);
+    assert.equal(initial.companies.length, 1312);
+    assert.equal(initial.evidence.length, 5354);
+    assert.equal(initial.observations.length, 495);
+    const businessReviews = initial.reviews.filter((review) => review.type === businessModelReviewType);
+    assert.equal(businessReviews.length, 26);
+    assert.deepEqual(businessReviews, seed.reviews.filter((review) => review.type === businessModelReviewType)
+      .sort((a, b) => a.id.localeCompare(b.id)),
+      "business model assessments and company/evidence links persist in the shared database");
     assert.deepEqual(initial.candidateBatches, seed.candidateBatches, "candidate gaps persist in the same database metadata");
     assert.deepEqual(initial.directoryRechecks, seed.directoryRechecks, "follow-up classifications persist without rewriting the discovery audit");
     assert.deepEqual(readResearchSnapshot(), initial, "reopening does not duplicate records");
@@ -64,9 +170,9 @@ test("research validation rejects broken evidence and unsafe source links", () =
 
 test("reviews link explicit companies without turning global or excluded cases into companies", () => {
   const snapshot = structuredClone(seed) as ResearchSnapshot;
-  assert.equal(snapshot.reviews.filter((r) => r.scope === "companies").length, 140);
-  assert.equal(snapshot.reviews.filter((r) => r.scope === "dataset").length, 12);
-  assert.equal(snapshot.reviews.filter((r) => r.scope === "excluded-candidate").length, 44);
+  assert.equal(snapshot.reviews.filter((r) => r.scope === "companies").length, 299);
+  assert.equal(snapshot.reviews.filter((r) => r.scope === "dataset").length, 159);
+  assert.equal(snapshot.reviews.filter((r) => r.scope === "excluded-candidate").length, 65);
   const review = snapshot.reviews.find((r) => r.id === "R4")!;
   assert.deepEqual(reviewCompanyIds(snapshot, review), ["AI007", "AI013", "AI021", "AI034"]);
   assert.deepEqual(reviewCompanyIds(snapshot, snapshot.reviews.find((r) => r.id === "CN-R-PSI")!), []);
@@ -85,11 +191,11 @@ test("reviews link explicit companies without turning global or excluded cases i
 test("disclosure counts exclude client income, biographies, targets and duplicate milestones", () => {
   const snapshot = seed as ResearchSnapshot;
   const summary = categorySummary(snapshot);
-  assert.equal(summary.reduce((n, c) => n + c.count, 0), 1051);
-  assert.equal(summary.reduce((n, c) => n + c.self, 0), 49);
+  assert.equal(summary.reduce((n, c) => n + c.count, 0), 1312);
+  assert.equal(summary.reduce((n, c) => n + c.self, 0), 63);
   assert.equal(summary.reduce((n, c) => n + c.estimate, 0), 2);
   assert.equal(summary.reduce((n, c) => n + c.platform, 0), 19);
-  assert.equal(summary.reduce((n, c) => n + c.unknown, 0), 981);
+  assert.equal(summary.reduce((n, c) => n + c.unknown, 0), 1228);
   assert.equal(snapshot.companies.find((c) => c.name === "Rork")?.revenueStatus, "unknown");
   assert.equal(snapshot.companies.find((c) => c.name === "Result")?.revenueStatus, "unknown");
   assert.ok(snapshot.observations.filter((o) => o.selection === "signal").every((o) => o.scope === "公司整体"));
@@ -124,8 +230,8 @@ test("service run rates, legacy freight revenue and paid adoption do not become
 
 test("technical reviews keep accessible materials separate from tested capabilities", () => {
   const snapshot = structuredClone(seed) as ResearchSnapshot;
-  assert.equal(snapshot.companies.filter((c) => c.technicalReview).length, 65);
-  assert.equal(snapshot.companies.filter((c) => c.technicalReview?.level === "public-artifact").length, 9);
+  assert.equal(snapshot.companies.filter((c) => c.technicalReview).length, 303);
+  assert.equal(snapshot.companies.filter((c) => c.technicalReview?.level === "public-artifact").length, 29);
   assert.equal(snapshot.companies.filter((c) => c.technicalReview?.level === "independent-test").length, 1);
   assert.equal(snapshot.companies.find((c) => c.id === "AI051")?.revenueStatus, "unknown");
   assert.match(snapshot.companies.find((c) => c.id === "AI051")!.technicalReview!.testScope!, /Sep 2026/);
@@ -198,9 +304,15 @@ test("ambiguous ARR claims retain currency, precision and attribution limits", (
   const portfolio = snapshot.observations.filter((o) => o.company === "AI100");
   assert.deepEqual(portfolio.filter((o) => o.selection === "signal").map((o) => o.id), ["SR25-O-DRS-PORTFOLIO"],
     "a product milestone must not be added to its company portfolio as another company");
-  assert.ok(snapshot.observations.filter((o) => o.id.startsWith("SR25-O-")).every((o) =>
-    o.unit !== "USD" && !o.metric && !o.observedAt && o.comparisonGroup === null),
+  const speedrun2025 = snapshot.observations.filter((o) => o.id.startsWith("SR25-O-"));
+  assert.ok(speedrun2025.every((o) =>
+    o.unit !== "USD" && !o.observedAt && o.comparisonGroup === null),
   "access dates and dollar symbols must not invent dated USD income samples");
+  assert.deepEqual(speedrun2025.filter((o) => o.metric).map((o) => [o.id, o.metric]).sort(),
+    [["SR25-O-DRS-PORTFOLIO", "arr"], ["SR25-O-LOOPS-ARR", "arr"]],
+    "explicit company ARR claims retain their metric without inferring currency or reporting dates");
+  assert.ok(platformIncomeSample(snapshot, { windowDays: null }).points.every((point) =>
+    !point.observation.id.startsWith("SR25-O-")), "undated ARR claims never enter platform MRR comparisons");
 });
 
 // Retractions and forecasts must stay visible for review without becoming revenue signals.
@@ -251,6 +363,10 @@ test("directory coverage reconciles every candidate and keeps profile-only incom
       assert.equal(row.foundedYear, 2026, "original Native discovery remains unchanged");
       assert.equal(company.year, null, "a model launch and YC date cannot settle the older business founding year");
       assert.ok(snapshot.reviews.some((review) => review.id === "NATIVE-R-COHORT" && review.companyIds?.includes(company.id)));
+    } else if (company.id === "YC31470") {
+      assert.equal(row.foundedYear, 2025, "original Tasklet discovery remains unchanged");
+      assert.equal(company.year, null, "a new product cannot establish a new company founding year");
+      assert.ok(snapshot.reviews.some((review) => review.id === "ENTERPRISE3-R-TASKLET" && review.companyIds?.includes(company.id)));
     } else {
       assert.equal(company.year, row.foundedYear);
       assert.ok([2025, 2026].includes(company.year!));
@@ -329,7 +445,7 @@ test("platform samples exclude stale data and keep ARR, estimates and collection
   const invalid = structuredClone(snapshot);
   invalid.observations = invalid.observations.filter((o) => o.company === "MR001" && o.metric === "mrr");
   const first = invalid.observations[0];
-  invalid.observations.push({ ...first, id: "future", observedAt: "2026-11-01", value: 999999 });
+  invalid.observations.push({ ...first, id: "future", observedAt: "2026-11-02", value: 999999 });
   invalid.observations.push({ ...first, id: "bad-date", observedAt: "2026-02-30", value: 999999 });
   invalid.observations.push({ ...first, id: "currency", unit: "EUR", value: 999999 });
   invalid.observations.push({ ...first, id: "older", observedAt: "2026-10-28", value: 1 });
@@ -375,6 +491,356 @@ test("product launch candidates preserve unresolved years and many launches per
   assert.throws(() => validateResearch(snapshot), /research candidate/);
 });
 
+test("the public SR007 roster preserves unique entries and Alven's older operator conflict", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((item) => item.id === "SR007-public-roster-2026-1")!;
+  assert.equal(batch.complete, false, "one public default cohort is not all source coverage");
+  assert.equal(batch.records.length, 79);
+  assert.equal(new Set(batch.records.map((row) => row.url)).size, 79);
+  const alven = batch.records.find((row) => row.name === "Alven")!;
+  assert.equal(alven.status, "pending-year");
+  assert.equal(alven.companyId, undefined);
+  assert.ok(alven.evidenceIds?.includes("SR007R-ALVEN-REG"));
+  assert.ok(!snapshot.observations.some((item) => item.evidence.startsWith("SR007R-")),
+    "roster claims, deployment plans and per-unit prices are not new financial observations");
+  const coherence = batch.records.find((row) => row.name === "Coherence Health")!;
+  assert.equal(coherence.status, "pending-ai", "a new coaching business still needs current AI delivery evidence");
+  assert.equal(coherence.companyId, undefined);
+  const followup = snapshot.observations.filter((item) => item.id.startsWith("SR007F2-"));
+  assert.equal(followup.length, 4);
+  assert.ok(followup.every((item) => ["excluded", "adoption"].includes(item.selection) && !item.metric && !item.observedAt));
+  assert.ok(!arrDisclosures(snapshot).some(({ observation }) => observation.id.startsWith("SR007F2-")),
+    "contracted ARR and pipeline are not live ARR disclosures");
+  const thirdFollowup = snapshot.observations.filter((item) => item.id.startsWith("SR007F3-"));
+  assert.equal(thirdFollowup.length, 6);
+  assert.equal(thirdFollowup.filter((item) => item.selection === "excluded").length, 3);
+  assert.equal(thirdFollowup.filter((item) => item.selection === "adoption").length, 3);
+  assert.ok(thirdFollowup.every((item) => !item.metric && !item.observedAt));
+  assert.ok(!arrDisclosures(snapshot).some(({ observation }) => observation.id.startsWith("SR007F3-")),
+    "projected ARR, connected customer assets and prospective contracts are not realized ARR");
+  assert.equal(snapshot.companies.find((item) => item.id === "AI121")!.cat, "C02",
+    "training data and environments are infrastructure rather than demonstrated foundation models");
+  const embrasure = snapshot.companies.find((item) => item.id === "AI122")!;
+  assert.equal(embrasure.technicalReview!.level, "public-artifact");
+  assert.ok(embrasure.technicalReview!.evidenceIds.includes("SR007F3-EMBRASURE-FLOW"),
+    "the public connector supports artifact availability, not independently reproduced warehouse performance");
+  for (const name of ["KIRA", "Leonidas", "Mecone", "PhotonSpear"]) {
+    const candidate = batch.records.find((row) => row.name === name)!;
+    assert.equal(candidate.status, "pending-ai",
+      "serving AI customers or using software controls is not evidence of an AI business");
+    assert.equal(candidate.companyId, undefined);
+  }
+  const maestroClaims = arrDisclosures(snapshot).filter(({ company }) => company.id === "AI130");
+  assert.equal(maestroClaims.length, 2, "keep the two original ARR milestones in the evidence ledger");
+  assert.ok(maestroClaims.every(({ observation }) => observation.selection === "historical" &&
+    arrFieldGaps(observation, snapshot.asOf).includes("date") &&
+    arrFieldGaps(observation, snapshot.asOf).includes("currency")));
+  const cumulative = snapshot.observations.find((item) => item.id === "SR007F4-O-MAESTRO-CUMULATIVE")!;
+  assert.equal(cumulative.selection, "historical");
+  assert.equal(cumulative.metric, undefined, "nine-month cumulative revenue cannot become ARR");
+  const contracted = snapshot.observations.find((item) => item.id === "SR007F4-O-HOID-CONTRACT")!;
+  assert.equal(contracted.selection, "excluded");
+  assert.equal(contracted.metric, undefined, "contracted run rate is not realized ARR");
+  const openwhispr = snapshot.companies.find((item) => item.id === "AI135")!;
+  assert.equal(openwhispr.technicalReview!.level, "public-artifact");
+  assert.ok(openwhispr.technicalReview!.evidenceIds.includes("SR007F5-OPENWHISPR-REPO"));
+  const voiceArr = arrDisclosures(snapshot).find(({ company }) => company.id === openwhispr.id)!.observation;
+  assert.equal(voiceArr.value, 120000);
+  assert.equal(voiceArr.bound, "≥");
+  assert.ok(arrFieldGaps(voiceArr, snapshot.asOf).includes("date"));
+  assert.ok(arrFieldGaps(voiceArr, snapshot.asOf).includes("currency"),
+    "current plan prices cannot supply the currency of an undated investor ARR claim");
+  const voiceUsers = snapshot.observations.find((item) => item.id === "SR007F5-O-OPENWHISPR-DAU")!;
+  assert.equal(voiceUsers.selection, "adoption", "daily active users are not paying subscribers");
+  assert.equal(voiceUsers.metric, undefined);
+  const salesLive = snapshot.observations.find((item) => item.id === "SR007F6-O-OTHELLO-LIVE")!;
+  assert.equal(salesLive.metric, "arr");
+  assert.equal(salesLive.value, 600000, "live ARR must not include contracted ARR or pipeline");
+  for (const suffix of ["CONTRACT", "PIPELINE"]) {
+    const prospective = snapshot.observations.find((item) => item.id === `SR007F6-O-OTHELLO-${suffix}`)!;
+    assert.equal(prospective.selection, "excluded");
+    assert.equal(prospective.metric, undefined);
+  }
+  const professionalService = snapshot.observations.find((item) => item.id === "SR007F6-O-PARCA-RUNRATE")!;
+  assert.equal(professionalService.metric, "annualized-revenue");
+  assert.equal(professionalService.selection, "historical");
+  assert.ok(!arrDisclosures(snapshot).some(({ observation }) => observation.id === professionalService.id),
+    "annualized professional-service revenue is not recurring subscription ARR");
+  assert.equal(snapshot.companies.find((item) => item.id === "AI137")!.technicalReview!.level, "description",
+    "a preliminary external ranking with unresolved methodology is not complete independent verification");
+  const contractFollowup = snapshot.observations.filter((item) => item.id.startsWith("SR007F7-"));
+  assert.equal(contractFollowup.filter((item) => item.selection === "excluded").length, 4);
+  assert.equal(contractFollowup.filter((item) => item.selection === "adoption").length, 1);
+  assert.ok(contractFollowup.every((item) => !item.metric && !item.observedAt));
+  assert.ok(!arrDisclosures(snapshot).some(({ observation }) => observation.id.startsWith("SR007F7-")),
+    "contracted revenue and potential customers' active users cannot become realized ARR");
+  assert.equal(snapshot.companies.find((item) => item.id === "AI144")!.revenueStatus, "unknown",
+    "free current SDK terms and a contracted ARR claim need reconciliation before labeling realized revenue");
+  const scaledrive = batch.records.find((row) => row.name === "scaledrive.ai")!;
+  assert.equal(scaledrive.status, "outside-cohort", "SR007 membership cannot replace a stated 2024 founding year");
+  assert.equal(scaledrive.companyId, undefined);
+  assert.ok(scaledrive.evidenceIds?.includes("SR007F8-SCALEDRIVE-SR"));
+  for (const id of ["AI147", "AI150"]) {
+    assert.equal(snapshot.companies.find((item) => item.id === id)!.technicalReview!.level, "description",
+      "self-hosting and SDK documentation do not establish correctly attributed public source code");
+    assert.equal(snapshot.companies.find((item) => item.id === id)!.revenueStatus, "unknown");
+  }
+  assert.ok(!arrDisclosures(snapshot).some(({ observation }) => observation.id.startsWith("SR007F8-")),
+    "previous-company ARR and financial amounts in document demonstrations are not current revenue");
+  assert.equal(batch.records.filter((row) => row.status === "linked").length, 71);
+  assert.equal(batch.records.filter((row) => row.profileStatus === "archive-only").length, 0,
+    "all reused independent profiles have now been explicitly reread");
+  assert.equal(batch.records.filter((row) => row.profileStatus === "readable").length, 79);
+  const ninthFollowup = snapshot.observations.filter((item) => item.id.startsWith("SR007F9-"));
+  assert.equal(ninthFollowup.length, 10);
+  assert.equal(ninthFollowup.filter((item) => item.selection === "excluded").length, 6);
+  assert.equal(ninthFollowup.filter((item) => item.selection === "adoption").length, 3);
+  const industrialRunRate = ninthFollowup.find((item) => item.id === "SR007F9-O-VALENT-ANNUALIZED")!;
+  assert.equal(industrialRunRate.metric, "annualized-revenue");
+  assert.equal(industrialRunRate.selection, "historical");
+  assert.ok(ninthFollowup.every((item) => !item.observedAt),
+    "access dates and weeks since launch cannot supply precise financial dates");
+  assert.ok(ninthFollowup.filter((item) => item !== industrialRunRate).every((item) => !item.metric));
+  assert.ok(!arrDisclosures(snapshot).some(({ observation }) => observation.id.startsWith("SR007F9-")),
+    "annual contracts without fulfillment evidence, funding, annualized revenue and pipeline remain outside live ARR");
+  for (const id of ["AI152", "AI158"]) {
+    assert.equal(snapshot.companies.find((item) => item.id === id)!.revenueStatus, "unknown",
+      "contracted labels alone cannot establish realized revenue");
+  }
+  assert.equal(snapshot.companies.find((item) => item.id === "AI161")!.cat, "C02",
+    "enterprise workload model specialization is classified by delivery rather than frontier-model slogans");
+  const rereadProfiles = snapshot.evidence.filter((item) => item.id.startsWith("SR007F10-P-"));
+  assert.equal(rereadProfiles.length, 17);
+  assert.equal(new Set(rereadProfiles.map((item) => item.companyId)).size, 17);
+  for (const evidence of rereadProfiles) {
+    const candidate = batch.records.find((row) => row.companyId === evidence.companyId)!;
+    assert.equal(candidate.url, evidence.url);
+    assert.ok(candidate.evidenceIds?.includes(evidence.id), "each reread has an exact profile link");
+  }
+  assert.ok(!snapshot.observations.some((item) => item.id.startsWith("SR007F10-")),
+    "rereading existing financial milestones must not introduce duplicate observations");
+  for (const id of ["AI067", "AI069"]) {
+    assert.equal(snapshot.companies.find((item) => item.id === id)!.cat, "C02",
+      "current hosted-model and training-data delivery are infrastructure");
+  }
+  const oldWorkflowArr = snapshot.observations.find((item) => item.id === "SR-O-AI069-arr")!;
+  assert.equal(oldWorkflowArr.evidence, "SR-E-infragrid", "retain the original workflow revenue evidence");
+  assert.equal(oldWorkflowArr.value, 302000);
+  assert.equal(oldWorkflowArr.observedAt, undefined);
+  assert.ok(snapshot.companies.find((item) => item.id === "AI069")!.notes.includes("历史ARR归属不清"),
+    "a current category change must retain the unresolved historical product attribution");
+});
+
+test("public Speedrun cohort rosters preserve the finite boundary without inventing founding years", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const rosters = snapshot.candidateBatches!.filter((batch) => /^SR00[1-7]-public-roster-2026-1$/.test(batch.id));
+  assert.equal(rosters.length, 7);
+  for (const [index, count] of [25, 25, 32, 42, 59, 59, 79].entries()) {
+    const batch = rosters.find((item) => item.id.startsWith(`SR${String(index + 1).padStart(3, "0")}-`))!;
+    assert.equal(batch.records.length, count);
+    assert.equal(batch.complete, false, "a complete directory page is not completed company-level research");
+  }
+  const rows = rosters.flatMap((batch) => batch.records);
+  assert.equal(rows.length, 321);
+  assert.equal(new Set(rows.map((row) => row.url)).size, 321);
+  const newlyRegistered = rosters.filter((batch) => !batch.id.startsWith("SR007-")).flatMap((batch) => batch.records);
+  assert.equal(newlyRegistered.length, 242);
+  assert.equal(newlyRegistered.filter((row) => row.status === "pending-year").length, 5);
+  assert.equal(newlyRegistered.filter((row) => row.status === "linked").length, 68);
+  assert.equal(newlyRegistered.filter((row) => row.status === "existing-outside-cohort").length, 1);
+  assert.equal(newlyRegistered.filter((row) => row.status === "outside-cohort").length, 144);
+  assert.equal(newlyRegistered.filter((row) => row.status === "pending-ai").length, 24,
+    "a known self-reported founding year does not by itself establish the current AI business");
+  assert.equal(newlyRegistered.filter((row) => row.profileStatus === "readable").length, 232);
+  assert.ok(newlyRegistered.filter((row) => row.status === "outside-cohort").every((row) =>
+    row.profileStatus === "readable" && row.evidenceIds?.some((id) => (id.startsWith("SRALL1-P-") || id.startsWith("SRPRO1-P-")))),
+  "old founding years require independent profile evidence, not cohort age");
+  const variants = newlyRegistered.filter((row) => row.name === "Variant");
+  assert.equal(variants.length, 2);
+  assert.equal(new Set(variants.map((row) => row.url)).size, 2, "same-name profiles must not be merged by name");
+  assert.equal(variants.filter((row) => row.companyId === "AI066").length, 1);
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SRALL1-")),
+    "roster discovery and outside-cohort claims do not create financial observations");
+  const profiles = snapshot.evidence.filter((row) => row.id.startsWith("SRPRO1-P-"));
+  assert.equal(profiles.length, 226);
+  for (const proof of profiles) {
+    const candidate = newlyRegistered.find((row) => row.id === proof.id.slice("SRPRO1-P-".length))!;
+    assert.equal(candidate.url, proof.url);
+    assert.ok(candidate.evidenceIds?.includes(proof.id));
+  }
+  for (const id of ["AI162", "AI163", "AI164", "AI165", "AI166", "AI167"]) {
+    const company = snapshot.companies.find((row) => row.id === id)!;
+    assert.equal(company.year, 2025);
+    assert.equal(company.revenueStatus, "unknown");
+    assert.equal(company.technicalReview!.level, "description");
+  }
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SRPRO1-")),
+    "future GPU capacity, free trials, customer savings and unread financial claims are not realized revenue");
+});
+
+test("Speedrun brand dates and survey benchmark scores do not create new-company revenue", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const rows = snapshot.candidateBatches!.flatMap((batch) => batch.records);
+  for (const id of ["SR004R-C11", "SR004R-C20"]) {
+    const row = rows.find((item) => item.id === id)!;
+    assert.equal(row.status, "pending-year", "a known brand year must retain unresolved underlying entity dates");
+    assert.equal(row.companyId, undefined);
+    assert.ok(row.evidenceIds!.some((proof) => proof.startsWith("SR004F2-")));
+  }
+  for (const id of ["SR004R-C08", "SR004R-C15"]) {
+    assert.equal(rows.find((item) => item.id === id)!.status, "pending-ai");
+  }
+  for (const [id, category] of [["AI168", "C06"], ["AI169", "C05"]]) {
+    const company = snapshot.companies.find((item) => item.id === id)!;
+    assert.equal(company.cat, category);
+    assert.equal(company.revenueStatus, "unknown");
+    assert.equal(company.technicalReview!.level, "description");
+  }
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SR004F2-")),
+    "brand-deal opportunities, listed fees and survey agreement are not financial observations");
+  const model = snapshot.reviews.find((row) => row.id === "MODEL1-SIMULATION-PANEL")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, model), ["AI169"]);
+  assert.ok(model.evidenceIds.includes("SR004F2-REHEARSALS-PRICE"));
+});
+
+test("recruiting service adoption and official balance sheets do not become ARR", () => {
+  const snapshot = seed as ResearchSnapshot;
+  for (const id of ["AI170", "AI171", "AI172", "AI173", "AI174", "AI175"]) {
+    const company = snapshot.companies.find((row) => row.id === id)!;
+    assert.equal(company.year, 2025);
+    assert.equal(company.revenueStatus, "unknown");
+    assert.equal(company.technicalReview!.level, "description");
+  }
+  const accounts = snapshot.evidence.find((row) => row.id === "SR005F3-DEX-ACCOUNTS")!;
+  assert.equal(accounts.companyId, "AI171");
+  assert.equal(new URL(accounts.url).hostname, "find-and-update.company-information.service.gov.uk");
+  assert.equal(accounts.publishedAt, "2026-09-08", "filing date is preserved without becoming a revenue measurement date");
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SR005F3-")),
+    "balance-sheet cash, client quotes, salaries and recruiting outcomes do not disclose revenue");
+  const model = snapshot.reviews.find((row) => row.id === "MODEL1-RECRUITING-SERVICE")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, model), ["AI175", "AI171"]);
+  assert.ok(model.evidenceIds.includes("SR005F3-JOOBA-TERMS"));
+});
+
+test("current products preserve unresolved identity and separate trading from software revenue", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const presia = snapshot.candidateBatches!.flatMap((batch) => batch.records)
+    .find((row) => row.id === "SR005R-C44")!;
+  assert.equal(presia.status, "pending-ai");
+  assert.equal(presia.companyId, undefined, "a reused domain does not resolve a changed business entity");
+  assert.ok(presia.evidenceIds!.includes("SR005F4-PRESIA-ASSET"));
+  for (const id of ["AI176", "AI177", "AI178", "AI179", "AI180"]) {
+    const company = snapshot.companies.find((row) => row.id === id)!;
+    assert.equal(company.revenueStatus, "unknown");
+  }
+  const syzygy = snapshot.companies.find((row) => row.id === "AI180")!;
+  assert.equal(syzygy.technicalReview!.level, "public-artifact");
+  assert.ok(syzygy.technicalReview!.evidenceIds.includes("SR005F4-SYZYGY-FILES"));
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SR005F4-")),
+    "landed prices, customer savings, model scores and listed subscriptions are not reported ARR");
+  const supply = snapshot.reviews.find((row) => row.id === "MODEL1-PHYSICAL-SUPPLY")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, supply), ["AI179"]);
+  assert.ok(snapshot.reviews.find((row) => row.id === "MODEL1-LOCAL-CLOUD")!.companyIds!.includes("AI180"));
+});
+
+test("new founding-year reports retain beta, academic and self-reported enforcement boundaries", () => {
+  const snapshot = seed as ResearchSnapshot;
+  for (const id of ["AI181", "AI182", "AI184", "AI185", "AI186"]) {
+    const company = snapshot.companies.find((row) => row.id === id)!;
+    assert.equal(company.year, 2026);
+    assert.equal(company.revenueStatus, "unknown");
+    assert.equal(company.technicalReview!.level, "description");
+  }
+  assert.equal(snapshot.companies.find((row) => row.id === "AI183")!.year, 2025);
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SR006F5-")),
+    "trial credits, customer revenue impact, demonstration fundraises and normalized research scores are not ARR");
+  const research = snapshot.reviews.find((row) => row.id === "SR006F5-R-RESEARCH")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, research), ["AI185", "AI169"]);
+  assert.ok(research.evidenceIds.includes("SR004F2-REHEARSALS-BENCH"));
+  const pricing = snapshot.reviews.find((row) => row.id === "MODEL1-MESSAGE-ENFORCEMENT")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, pricing), ["AI186"]);
+  assert.ok(pricing.evidenceIds.includes("SR006F5-ZERODRIFT-TERMS"));
+});
+
+test("rebrands and ambiguous monthly receipts stay outside comparable ARR", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const rows = snapshot.candidateBatches!.flatMap((batch) => batch.records);
+  for (const id of ["SR006R-C37", "SR006R-C54"]) {
+    const row = rows.find((item) => item.id === id)!;
+    assert.equal(row.status, "pending-year");
+    assert.equal(row.companyId, undefined, "brand dates must not overwrite existing legal-entity dates");
+  }
+  const idilio = rows.find((item) => item.id === "SR006R-C22")!;
+  assert.equal(idilio.status, "pending-ai");
+  assert.ok(idilio.evidenceIds!.includes("SR006F6-IDILIO-SR"));
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SR006F6-")),
+    "pipeline, retained client revenue, illustrative tax values and undated monthly receipts are not comparable ARR");
+  for (const id of ["AI187", "AI188", "AI189"]) {
+    assert.equal(snapshot.companies.find((row) => row.id === id)!.revenueStatus, "unknown");
+  }
+  const tax = snapshot.reviews.find((row) => row.id === "MODEL1-TAX-PREP")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, tax), ["AI188"]);
+  assert.ok(tax.evidenceIds.includes("SR006F6-GROVE-PRICE"));
+});
+
+test("care and legal delivery preserve financial exclusions and linked cost reviews", () => {
+  const snapshot = seed as ResearchSnapshot;
+  for (const id of ["AI190", "AI191", "AI192", "AI193", "AI194", "AI195"]) {
+    const company = snapshot.companies.find((row) => row.id === id)!;
+    assert.equal(company.revenueStatus, "unknown");
+    assert.equal(company.technicalReview!.level, "description");
+    const candidate = snapshot.candidateBatches!.flatMap((batch) => batch.records)
+      .find((row) => row.companyId === id)!;
+    assert.equal(candidate.status, "linked");
+    assert.equal(candidate.categoryId, company.cat);
+    assert.ok(company.evidenceIds.every((proof) => snapshot.evidence.some((row) => row.id === proof && row.companyId === id)));
+  }
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SRCARE1-")),
+    "undefined annual run rate, customer savings, list prices and usage are not comparable ARR");
+  const hardware = snapshot.reviews.find((row) => row.id === "MODEL1-HARDWARE-LIFETIME")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, hardware), ["AI195"]);
+  const clinical = snapshot.reviews.find((row) => row.id === "MODEL1-CARE-OPERATIONS")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, clinical), ["AI191", "AI194"]);
+});
+
+test("enterprise contracts and launch-year conflicts retain their exclusions", () => {
+  const snapshot = structuredClone(seed) as ResearchSnapshot;
+  const accelerator = snapshot.candidateBatches!.flatMap((batch) => batch.records)
+    .find((row) => row.id === "SR006R-C01")!;
+  assert.equal(accelerator.status, "pending-year");
+  assert.equal(accelerator.companyId, undefined);
+  assert.ok(accelerator.evidenceIds!.includes("SRENTER1-ACCELER8-DEALROOM"));
+  for (const [id, value, bound] of [["HEAVI", 100000, "="], ["VERRA", 700000, "≈"]] as const) {
+    const contract = snapshot.observations.find((row) => row.id === `SRENTER1-O-${id}-CONTRACT`)!;
+    assert.equal(contract.value, value);
+    assert.equal(contract.bound, bound);
+    assert.equal(contract.selection, "excluded");
+    assert.equal(contract.observedAt, undefined);
+    assert.equal(contract.comparisonGroup, null);
+    assert.equal(snapshot.companies.find((row) => row.id === contract.company)!.revenueStatus, "unknown");
+    contract.metric = "arr";
+    assert.ok(!arrDisclosures(snapshot).some((row) => row.observation.id === contract.id),
+      "even a wrongly added ARR label must not promote an excluded contract");
+    assert.ok(!platformIncomeSample(snapshot, { windowDays: 90 }).points
+      .some((row) => row.observation.id === contract.id));
+  }
+});
+
+test("financial candidates need current AI evidence before they acquire company and income links", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const candidates = snapshot.candidateBatches!.flatMap((batch) => batch.records);
+  for (const id of ["SR006R-C06", "SR006R-C16", "SR005R-C35", "SR006R-C08"]) {
+    const candidate = candidates.find((row) => row.id === id)!;
+    assert.equal(candidate.status, "pending-ai");
+    assert.equal(candidate.companyId, undefined);
+    assert.ok(candidate.evidenceIds!.some((proof) => proof.startsWith("SRFIN1-")));
+  }
+  const financial = snapshot.reviews.find((row) => row.id === "MODEL1-FINANCIAL-OPERATIONS")!;
+  assert.deepEqual(reviewCompanyIds(snapshot, financial), ["AI202", "AI203", "AI204"]);
+  assert.ok(!snapshot.observations.some((row) => row.evidence.startsWith("SRFIN1-")),
+    "bank size, FX processing, artist revenue, demo portfolios and benchmark scores are not vendor income");
+});
+
 test("annual launch archives exclude older companies only with evidence and reuse existing records", () => {
   const snapshot = structuredClone(seed) as ResearchSnapshot;
   const batch = snapshot.candidateBatches!.find((b) => b.id === "PH-2025-visible-1")!;
@@ -402,7 +868,7 @@ test("unreconciled directory financials remain source reviews instead of income
   assert.ok(review.evidenceIds.includes("PH-TANA-DR"));
   assert.equal(reviewCompanyIds(snapshot, review).length, 0);
   assert.ok(!snapshot.observations.some((o) => o.evidence === "PH-TANA-DR"));
-  assert.equal(snapshot.candidateBatches!.flatMap((b) => b.records).filter((r) => r.status === "pending-year").length, 18);
+  assert.equal(snapshot.candidateBatches!.flatMap((b) => b.records).filter((r) => r.status === "pending-year").length, 136);
 });
 
 test("product pivots and founder histories do not become new company years or current revenue", () => {
@@ -439,6 +905,337 @@ test("follow-up evidence can admit an uncertain directory candidate without rewr
   assert.throws(() => validateResearch(snapshot), /directory recheck/);
 });
 
+test("AI relevance follow-ups retain unresolved businesses and reuse existing company identities", () => {
+  const snapshot = structuredClone(seed) as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-1")!;
+  assert.equal(batch.complete, false);
+  assert.equal(batch.records.length, 24);
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear").slice(0, 24);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  const linked = batch.records.filter((r) => r.status === "linked");
+  assert.equal(linked.length, 17);
+  assert.equal(linked.filter((r) => r.companyId!.startsWith("YC")).length, 14);
+  for (const [name, id] of [["Bud", "AI070"], ["Prism", "AI030"], ["Parametric", "AI014"]]) {
+    assert.equal(linked.find((r) => r.name === name)?.companyId, id);
+  }
+  assert.equal(snapshot.companies.filter((c) => c.profileOnly || c.directoryOrigin === "yc-2025-2026").length, 928);
+  for (const row of linked) {
+    const ycId = Number(row.id.replace("YC-AI1-", ""));
+    assert.equal(snapshot.directoryRechecks!.find((r) => r.ycId === ycId)?.companyId, row.companyId);
+  }
+  const pending = batch.records.filter((r) => r.status === "pending-ai");
+  assert.equal(pending.length, 7);
+  assert.ok(pending.every((r) => !r.companyId && r.evidenceIds!.length && /2025/.test(r.note)));
+  assert.match(pending.find((r) => r.name === "Better Auth")!.note, /AI.*模块/);
+  validateResearch(snapshot);
+  pending[0].companyId = "AI014";
+  assert.throws(() => validateResearch(snapshot), /research candidate/);
+  delete pending[0].companyId;
+  pending[0].evidenceIds = [];
+  assert.throws(() => validateResearch(snapshot), /research candidate/);
+});
+
+test("historical monthly revenue and customer examples do not enter recurring platform comparisons", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const monthly = snapshot.observations.find((o) => o.id === "UNCLEAR1-O-SCALAR-MONTHLY")!;
+  assert.equal(monthly.value, 74000);
+  assert.equal(monthly.selection, "historical");
+  assert.equal(monthly.metric, undefined, "monthly revenue alone does not establish MRR or ARR");
+  assert.equal(monthly.comparisonGroup, null);
+  assert.equal(snapshot.companies.find((c) => c.id === "YC30514")!.revenueStatus, "self");
+  for (const id of ["AMBY-CLIENT", "NIXO-EXAMPLE", "AUTOSTEP-WASTE"]) {
+    assert.equal(snapshot.observations.find((o) => o.id === `UNCLEAR1-O-${id}`)!.selection, "excluded");
+  }
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR1-")));
+  const cua = snapshot.companies.find((c) => c.id === "YC30420")!;
+  assert.equal(cua.cat, "C03");
+  assert.equal(cua.revenueStatus, "unknown");
+  assert.match(cua.businessModel!, /自备计算机/);
+  assert.equal(cua.technicalReview!.level, "public-artifact");
+});
+
+test("a second uncertain cohort admits evidenced AI tasks while preserving autonomy and finance gaps", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-2")!;
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear").slice(24, 48);
+  assert.equal(batch.complete, false);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(batch.records.filter((r) => r.status === "linked").length, 14);
+  assert.equal(batch.records.filter((r) => r.status === "pending-ai").length, 10);
+  for (const name of ["Albacore Inc.", "Perseus Defense", "Munify", "Ruvo"]) {
+    const row = batch.records.find((r) => r.name === name)!;
+    assert.equal(row.status, "pending-ai");
+    assert.equal(row.companyId, undefined, "autonomy, a domain or finance automation alone is insufficient");
+    assert.ok(row.evidenceIds!.length);
+  }
+  const signals = snapshot.companies.find((c) => c.id === "YC30639")!;
+  assert.equal(signals.year, 2026, "retain the company year instead of assigning the batch's majority year");
+  assert.equal(signals.cat, "C06");
+  assert.equal(snapshot.companies.find((c) => c.id === "YC30846")!.cat, "C03");
+  assert.match(snapshot.companies.find((c) => c.id === "YC30821")!.business, /远端推理/);
+  assert.equal(snapshot.companies.find((c) => c.id === "YC30933")!.technicalReview!.level, "description",
+    "vendor clinical agreement is not an independent validation");
+  const amounts = snapshot.observations.filter((o) => o.id.startsWith("UNCLEAR2-"));
+  assert.equal(amounts.length, 8);
+  assert.ok(amounts.every((o) => ["excluded", "adoption"].includes(o.selection) && !o.metric && o.comparisonGroup === null));
+  assert.equal(amounts.find((o) => o.id.endsWith("WARDSTONE-GRANT"))!.selection, "excluded");
+  assert.equal(amounts.find((o) => o.id.endsWith("SOLVA-OLD-PREMIUM"))!.selection, "excluded");
+  assert.ok(batch.records.filter((r) => r.companyId).every((r) => snapshot.companies.find((c) => c.id === r.companyId)!.revenueStatus === "unknown"));
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR2-")));
+});
+
+test("the third uncertain cohort retains shutdowns, unknown scale and mixed data-service economics", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-3")!;
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear").slice(48, 72);
+  assert.equal(batch.complete, false);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(batch.records.filter((r) => r.status === "linked").length, 15);
+  assert.equal(batch.records.filter((r) => r.status === "pending-ai").length, 9);
+  for (const name of ["Mirabelle", "Kyten Technologies"]) {
+    assert.equal(batch.records.find((r) => r.name === name)!.companyId, undefined);
+  }
+  const klaus = snapshot.companies.find((c) => c.id === "YC31084")!;
+  assert.equal(klaus.revenueStatus, "unknown", "a shutdown must not manufacture a zero revenue report");
+  assert.match(klaus.stage, /2026-09-01停服/);
+  assert.ok(!snapshot.observations.some((o) => o.company === klaus.id));
+  const openspec = snapshot.companies.find((c) => c.id === "YC31116")!;
+  assert.equal(openspec.team, null, "missing staff count stays unknown");
+  assert.equal(openspec.year, 2025, "a license copyright line alone is not a company founding date");
+  assert.equal(openspec.technicalReview!.level, "public-artifact");
+  assert.match(snapshot.companies.find((c) => c.id === "YC31095")!.businessModel!, /清洁/);
+  const figures = snapshot.observations.filter((o) => o.id.startsWith("UNCLEAR3-"));
+  assert.equal(figures.length, 8);
+  assert.ok(figures.every((o) => ["excluded", "adoption"].includes(o.selection) && !o.metric && o.comparisonGroup === null));
+  assert.equal(figures.find((o) => o.id.endsWith("SHORTKIT-OLD-ARR"))!.selection, "excluded");
+  assert.equal(figures.find((o) => o.id.endsWith("KALPA-TRAIN-COST"))!.selection, "excluded");
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR3-")));
+});
+
+test("the fourth uncertain cohort distinguishes product pivots, managed labor and pass-through money", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-4")!;
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear").slice(72, 96);
+  assert.equal(batch.complete, false);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(batch.records.filter((r) => r.status === "linked").length, 15);
+  assert.equal(batch.records.filter((r) => r.status === "pending-ai").length, 9);
+  assert.equal(batch.records.find((r) => r.name === "Orthogonal")!.companyId, "AI036");
+  assert.equal(snapshot.companies.filter((c) => c.url.endsWith("/companies/orthogonal")).length, 1);
+  const fern = snapshot.companies.find((c) => c.id === "YC31152")!;
+  assert.equal(fern.cat, "C02");
+  assert.match(fern.notes, /会议/);
+  const mocha = snapshot.companies.find((c) => c.id === "YC31269")!;
+  assert.equal(mocha.year, 2026);
+  assert.match(mocha.businessModel!, /人工/);
+  assert.match(mocha.price, /Platform.*Managed/);
+  assert.match(mocha.notes, /Coming soon/);
+  const figures = snapshot.observations.filter((o) => o.id.startsWith("UNCLEAR4-"));
+  assert.equal(figures.length, 7);
+  assert.ok(figures.every((o) => ["excluded", "adoption"].includes(o.selection) && !o.metric && o.comparisonGroup === null));
+  for (const suffix of ["LAURENCE-ADSPEND", "EKPA-CONNECTED-ASSETS", "REGBASE-CLIENT-GRANTS", "MOCHA-FUNDING"]) {
+    assert.equal(figures.find((o) => o.id.endsWith(suffix))!.selection, "excluded");
+  }
+  assert.equal(snapshot.companies.find((c) => c.id === "YC31199")!.technicalReview!.level, "public-artifact");
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR4-")));
+});
+
+test("the fifth uncertain cohort separates dated ARR, service run rates, bookings and previous ventures", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-5")!;
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear").slice(96, 120);
+  assert.equal(batch.complete, false);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(batch.records.filter((r) => r.status === "linked").length, 17);
+  assert.equal(batch.records.filter((r) => r.status === "pending-ai").length, 7);
+  assert.equal(batch.records.find((r) => r.name === "primitive")!.companyId, "AI002");
+  assert.equal(batch.records.find((r) => r.name === "Result")!.companyId, "AI001");
+  const result = snapshot.companies.find((c) => c.id === "AI001")!;
+  assert.equal(result.cat, "C09");
+  assert.equal(result.revenueStatus, "unknown");
+  assert.match(result.notes, /280万美元ARR属于用户/);
+  assert.ok(result.evidenceIds.includes("UNCLEAR5-31438-TERMS"));
+  const andco = snapshot.companies.find((c) => c.id === "YC31411")!;
+  assert.equal(andco.year, 2026, "a founder's previous venture must not replace the new company's stated year");
+  assert.match(andco.notes, /Layup/);
+  assert.equal(snapshot.evidence.find((e) => e.id === "UNCLEAR5-31411-LAUNCH6")!.companyId, null);
+  const figures = snapshot.observations.filter((o) => o.id.startsWith("UNCLEAR5-"));
+  assert.equal(figures.length, 18);
+  const dated = figures.find((o) => o.id.endsWith("TRELLIS-ARR-AUG"))!;
+  assert.equal(dated.metric, "arr");
+  assert.equal(dated.observedAt, undefined, "a page maintenance date is not a financial cutoff");
+  assert.ok(arrFieldGaps(dated, snapshot.asOf).includes("date"));
+  assert.equal(dated.bound, "≥");
+  assert.equal(figures.find((o) => o.id.endsWith("INSTA-RUNRATE"))!.metric, "annualized-revenue");
+  assert.equal(figures.find((o) => o.id.endsWith("INSTA-LAUNCH-ARR"))!.metric, "arr");
+  for (const suffix of ["PARROT-CONTRACT", "KINRO-OLD-CONTRACT", "BENTO-OLD-EMPLOYER", "TRELLIS-OLD-MGMT"]) {
+    assert.equal(figures.find((o) => o.id.endsWith(suffix))!.selection, "excluded");
+  }
+  assert.equal(snapshot.companies.find((c) => c.id === "YC31423")!.technicalReview!.level, "description",
+    "an internal benchmark subset is not an independent leaderboard result");
+  assert.ok(figures.every((o) => o.comparisonGroup === null));
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR5-")));
+});
+
+test("the sixth uncertain cohort preserves namesakes, churn and historical robotics MRR", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-6")!;
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear").slice(120, 144);
+  assert.equal(batch.complete, false);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(batch.records.filter((r) => r.status === "linked").length, 13);
+  assert.equal(batch.records.filter((r) => r.status === "pending-ai").length, 11);
+  const hera = snapshot.companies.find((c) => c.id === "YC32123")!;
+  const videoHera = snapshot.companies.find((c) => c.id === "AI025")!;
+  assert.equal(hera.cat, "C07");
+  assert.equal(hera.year, 2026);
+  assert.equal(videoHera.cat, "C08");
+  assert.equal(videoHera.year, 2025);
+  assert.notEqual(hera.url, videoHera.url, "same-name products with different YC pages must not be merged");
+  for (const name of ["Aernata", "Maquoketa Research", "Fire Wallet", "Eden Robotics", "Edgerun"]) {
+    const row = batch.records.find((r) => r.name === name)!;
+    assert.equal(row.status, "pending-ai");
+    assert.equal(row.companyId, undefined, "historical AI products, agent features and autonomous hardware need current-core evidence");
+  }
+  const figures = snapshot.observations.filter((o) => o.id.startsWith("UNCLEAR6-"));
+  assert.equal(figures.length, 13);
+  const churn = figures.find((o) => o.id.endsWith("ARDENT-CHURN"))!;
+  assert.equal(churn.selection, "excluded");
+  assert.equal(churn.metric, undefined, "lost ARR is not a positive current ARR observation");
+  assert.equal(snapshot.companies.find((c) => c.id === "YC31475")!.revenueStatus, "unknown");
+  const mrr = figures.find((o) => o.id.endsWith("AVEA-MRR"))!;
+  assert.equal(mrr.value, 18000);
+  assert.equal(mrr.metric, "mrr");
+  assert.equal(mrr.selection, "historical");
+  assert.match(mrr.unit, /无币种/);
+  assert.match(snapshot.companies.find((c) => c.id === "YC31530")!.notes, /Acquired/);
+  for (const suffix of ["PLAN0-PROJECTS-YC", "PLAN0-PROJECTS-LAUNCH", "SILMARIL-DAMAGE-YC", "SILMARIL-DAMAGE-CASE1", "SILMARIL-DAMAGE-CASE2", "EXPANSE-WASTE"]) {
+    assert.equal(figures.find((o) => o.id.endsWith(suffix))!.selection, "excluded");
+  }
+  const openwork = snapshot.companies.find((c) => c.id === "YC31505")!;
+  assert.equal(openwork.technicalReview!.level, "public-artifact");
+  assert.ok(openwork.technicalReview!.evidenceIds.includes("UNCLEAR6-31505-EE-LICENSE"));
+  assert.match(openwork.notes, /桌面MIT与ee目录/);
+  assert.ok(figures.every((o) => o.comparisonGroup === null));
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR6-")));
+});
+
+test("the seventh uncertain cohort separates hardware sales, prepayments and bounded verification", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-7")!;
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear").slice(144, 168);
+  assert.equal(batch.complete, false);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(batch.records.filter((r) => r.status === "linked").length, 16);
+  assert.equal(batch.records.filter((r) => r.status === "pending-ai").length, 8);
+  const robotNori = snapshot.companies.find((c) => c.id === "YC32553")!;
+  const healthNori = snapshot.companies.find((c) => c.id === "YC30657")!;
+  assert.equal(robotNori.cat, "C10");
+  assert.equal(healthNori.cat, "C09");
+  assert.notEqual(robotNori.url, healthNori.url, "same-name hardware and health companies retain distinct identities");
+  assert.equal(batch.records.find((r) => r.name === "Nori")!.companyId, robotNori.id);
+  const figures = snapshot.observations.filter((o) => o.id.startsWith("UNCLEAR7-"));
+  assert.equal(figures.length, 18);
+  const sales = figures.find((o) => o.id.endsWith("NORI-SALES"))!;
+  assert.equal(sales.value, 440000);
+  assert.equal(sales.selection, "historical");
+  assert.equal(sales.metric, undefined, "hardware sales with unverified preorder/delivery mix must not become ARR");
+  assert.match(snapshot.companies.find((c) => c.id === "YC32164")!.price!, /额度/);
+  for (const suffix of ["GUT-PHARMACY", "MANIFOLD-PICKS", "ATC-CLIENT-FLEET", "OPERON-CLIENT-SAVE", "ANYALPHA-OLD-APPS", "LETTER-DEMO"]) {
+    assert.equal(figures.find((o) => o.id.endsWith(suffix))!.selection, "excluded");
+  }
+  assert.match(figures.find((o) => o.id.endsWith("LETTER-DEMO"))!.scope, /fictional/);
+  assert.equal(snapshot.companies.find((c) => c.id === "YC34899")!.cat, "C06");
+  const kailash = snapshot.companies.find((c) => c.id === "YC34828")!;
+  assert.equal(kailash.cat, "C10");
+  assert.equal(kailash.technicalReview!.level, "description", "an open-weights claim without readable weights or a model card is not a reviewed public artifact");
+  const graphify = snapshot.companies.find((c) => c.id === "YC32583")!;
+  assert.equal(graphify.technicalReview!.level, "public-artifact");
+  const proof = snapshot.evidence.find((e) => e.id === "UNCLEAR7-32583-PROOF")!;
+  assert.match(proof.summary, /unknown/);
+  assert.match(proof.summary, /函数/);
+  assert.match(proof.limitation, /整库正确/);
+  assert.match(snapshot.companies.find((c) => c.id === "YC32518")!.notes, /Build标Coming soon/);
+  for (const name of ["Kara", "Molagri", "TareBio", "Atomarine", "Vernius Systems, Inc."]) {
+    const row = batch.records.find((r) => r.name === name)!;
+    assert.equal(row.status, "pending-ai");
+    assert.equal(row.companyId, undefined);
+  }
+  assert.ok(figures.every((o) => o.comparisonGroup === null));
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR7-")));
+});
+
+test("all original AI-unclear candidates retain a unique follow-up without counting EveryApp twice", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const rows = snapshot.candidateBatches!.filter((b) => b.id.startsWith("YC-AI-UNCLEAR-")).flatMap((b) => b.records);
+  const original = coverageAudit.records.filter((r) => r.status === "ai-unclear");
+  assert.equal(rows.length, 192);
+  assert.equal(new Set(rows.map((r) => r.url)).size, 192);
+  assert.deepEqual(rows.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(rows.filter((r) => r.status === "linked").length, 118);
+  assert.equal(rows.filter((r) => r.status === "pending-ai").length, 74);
+  assert.equal(snapshot.directoryRechecks!.filter((r) => r.ycId === 36088).length, 1);
+  const everyapp = rows.find((r) => r.name === "EveryApp")!;
+  assert.equal(everyapp.companyId, "AI074");
+  assert.equal(snapshot.companies.filter((c) => c.id === "AI074").length, 1);
+  for (const row of rows.filter((r) => r.status === "pending-ai")) {
+    assert.equal(row.companyId, undefined);
+    assert.ok(row.evidenceIds!.length > 0, "unresolved AI relevance has explicit evidence and gaps");
+  }
+  assert.equal(snapshot.coverage!.newProfiles, 928, "later evidence does not rewrite the original discovery accounting");
+});
+
+test("the final uncertain cohort separates delivery-start rentals, reservations and upstream costs", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-AI-UNCLEAR-8")!;
+  assert.equal(batch.complete, false, "reading the full pool does not resolve all AI, year or financial gaps");
+  assert.equal(batch.records.filter((r) => r.status === "linked").length, 11);
+  assert.equal(batch.records.filter((r) => r.status === "pending-ai").length, 13);
+  const rhem = snapshot.companies.find((c) => c.id === "YC35127")!;
+  assert.match(rhem.price!, /确认交付后/);
+  assert.match(rhem.price!, /99 USD/);
+  assert.equal(rhem.revenueStatus, "unknown");
+  assert.match(snapshot.companies.find((c) => c.id === "YC37272")!.price!, /预约/);
+  assert.match(snapshot.companies.find((c) => c.id === "AI074")!.price!, /有效订阅/);
+  assert.match(snapshot.companies.find((c) => c.id === "YC35396")!.notes, /Coming next/);
+  assert.match(snapshot.companies.find((c) => c.id === "YC36774")!.notes, /Early access/);
+  const figures = snapshot.observations.filter((o) => o.id.startsWith("UNCLEAR8-"));
+  assert.equal(figures.length, 9);
+  assert.ok(figures.every((o) => ["excluded", "adoption"].includes(o.selection) && !o.metric && o.comparisonGroup === null));
+  for (const suffix of ["OASIVE-OLD-WELLS", "OASIVE-OLD-GOOGLE", "OBSESSION-CALCULATOR", "EVERYAPP-UPSTREAM"]) {
+    assert.equal(figures.find((o) => o.id.endsWith(suffix))!.selection, "excluded");
+  }
+  for (const name of ["Clean", "STASIS", "RATLOG", "Inflection Space Systems", "twentyfour26"]) {
+    assert.equal(batch.records.find((r) => r.name === name)!.status, "pending-ai");
+  }
+  assert.ok(!platformIncomeSample(snapshot, { windowDays: null }).points.some((p) => p.observation.id.startsWith("UNCLEAR8-")));
+});
+
+test("founding conflicts preserve old product history without creating new companies or revenue", () => {
+  const snapshot = seed as ResearchSnapshot;
+  const batch = snapshot.candidateBatches!.find((b) => b.id === "YC-DATE-CONFLICT-1")!;
+  const original = coverageAudit.records.filter((r) => r.status === "date-conflict");
+  assert.equal(batch.complete, false);
+  assert.equal(batch.records.length, 6);
+  assert.deepEqual(batch.records.map((r) => r.url), original.map((r) => r.source));
+  assert.equal(new Set(batch.records.map((r) => r.url)).size, original.length);
+  for (const row of batch.records) {
+    assert.equal(row.status, "pending-year");
+    assert.equal(row.companyId, undefined);
+    const evidence = snapshot.evidence.filter((e) => row.evidenceIds!.includes(e.id));
+    assert.equal(evidence.length, row.evidenceIds!.length);
+    assert.ok(evidence.every((e) => e.companyId === null));
+    assert.ok(evidence.some((e) => e.publishedAt?.startsWith("2025-")), "old product launch remains explicit");
+    assert.ok(!snapshot.companies.some((c) => c.evidenceIds.some((eid) => row.evidenceIds!.includes(eid))));
+  }
+  assert.match(batch.records.find((r) => r.name === "Layers")!.note, /未确认当前AI核心/);
+  assert.ok(!snapshot.observations.some((o) => o.evidence.startsWith("YEARCONFLICT1-")));
+  const excluded = coverageAudit.records.filter((r) => r.status === "year-outside-or-missing");
+  assert.equal(excluded.filter((r) => r.foundedYear === null).length, 54);
+  assert.equal(excluded.filter((r) => r.foundedYear !== null).length, 214);
+  assert.ok(excluded.filter((r) => r.foundedYear !== null).every((r) => ![2025, 2026].includes(r.foundedYear!)));
+});
+
 test("Chinese discovery entries preserve unread articles and use separate primary evidence", () => {
   const snapshot = structuredClone(seed) as ResearchSnapshot;
   const batch = snapshot.candidateBatches!.find((b) => b.id === "JQ-2026-targeted-1")!;

content/research/ai-income-analysis.json

@@ -1,6 +1,6 @@
 {
-  "sourceVersion": "2026-10-31-industry-11",
-  "asOf": "2026-10-31",
+  "sourceVersion": "2026-11-01-source-closeout-1",
+  "asOf": "2026-11-01",
   "metric": "platform-mrr-usd",
   "sampleUnit": "product-or-business",
   "note": "独立Python复算参考值，仅验证样本计算；不是行业估计或财务审计。",

scripts/audit-ai-research.py

@@ -4,7 +4,7 @@ from collections import Counter
 import json
 from pathlib import Path
 import sys
-from urllib.parse import urlsplit
+from urllib.parse import parse_qs, urlsplit
 
 ROOT = Path(__file__).resolve().parents[1]
 DATA = json.loads((ROOT / 'content/research/ai-companies.seed.json').read_text())
@@ -16,6 +16,20 @@ SOURCE_SLUG = 'ai-company-research/02-coverage-and-gaps'
 BASE = '/docs/other-research/ai-company-research/overview'
 
 
+def yc_coverage_summary():
+    companies = {row['id']: row for row in DATA['companies']}
+    imported = [companies[f"YC{row['ycId']}"] for row in AUDIT['records'] if row['status'] == 'imported']
+    profile_only = sum(bool(row.get('profileOnly')) for row in imported)
+    groups = {}
+    for label, prefix in [('unclearAI', 'YC-AI-UNCLEAR-'), ('missingYear', 'YC-MISSING-YEAR-'),
+                          ('dateConflict', 'YC-DATE-CONFLICT-')]:
+        rows = [row for batch in DATA.get('candidateBatches', []) if batch['id'].startswith(prefix)
+                for row in batch['records']]
+        groups[label] = {'records': len(rows), 'statuses': dict(sorted(Counter(row['status'] for row in rows).items()))}
+    return {'initialProfiles': len(AUDIT['records']), 'originalImported': len(imported),
+            'profileOnly': profile_only, 'deepenedOriginal': len(imported) - profile_only, **groups}
+
+
 
 def source_register():
     sources = SOURCES['sources']
@@ -26,6 +40,63 @@ def source_register():
     for source in sources:
         assert source['status'] in {'candidate-audit', 'targeted', 'pending', 'context', 'access-limited', 'per-company'}
         assert source['boundary'] and source['nextCheck']
+        if source['id'] == 'S01':
+            assert source.get('coverageSummary') == yc_coverage_summary(), 'YC source summary is stale'
+        if source['id'] == 'S14' and source.get('rosterAudit'):
+            roster = source['rosterAudit']
+            batch = next(batch for batch in DATA['candidateBatches'] if batch['id'] == roster['candidateBatchId'])
+            assert batch['sourceId'] == 'S14' and not batch['complete']
+            assert roster['defaultCohort'] == 'SR007' and roster['next'] is None
+            assert len(batch['records']) == roster['recordCount'] == roster['reportedCount']
+            assert len({row['url'] for row in batch['records']}) == roster['recordCount']
+        if source['id'] == 'S14' and source.get('publicRosterAudits'):
+            audits = source['publicRosterAudits']
+            assert {a['cohort'] for a in audits} == {f'SR{i:03d}' for i in range(1, 8)}
+            assert len(audits) == 7
+            profile_urls = []
+            for audit in audits:
+                batch = next(b for b in DATA['candidateBatches'] if b['id'] == audit['candidateBatchId'])
+                query = parse_qs(urlsplit(audit['url']).query)
+                assert urlsplit(audit['url']).netloc == 'speedrun.a16z.com'
+                assert query == {'limit': ['100'], 'offset': ['0'], 'cohort': [audit['cohort']]}
+                assert urlsplit(audit['url']).path == '/api/companies/companyparams'
+                assert audit['httpStatus'] == 200 and audit['accessedAt'] <= DATA['asOf']
+                assert audit['next'] is None and audit['previous'] is None
+                assert len(batch['records']) == audit['recordCount'] == audit['reportedCount']
+                assert audit['uniquePublicIds'] == audit['uniqueSlugs'] == audit['recordCount']
+                assert len(audit['responseSha256']) == 64 and all(c in '0123456789abcdef' for c in audit['responseSha256'])
+                assert batch['sourceId'] == 'S14' and not batch['complete']
+                proof = next(e for e in DATA['evidence'] if e['id'] == audit['evidenceId'])
+                assert proof['url'] == audit['url'] and proof['companyId'] is None
+                profile_urls.extend(row['url'] for row in batch['records'])
+            assert len(profile_urls) == len(set(profile_urls)), 'duplicate profiles across public cohorts'
+        if source['id'] == 'S14' and source.get('profileAudit'):
+            audit = source['profileAudit']
+            entries = audit['records']
+            candidates = {row['id']: row for b in DATA['candidateBatches'] for row in b['records']}
+            evidence_by_id = {row['id']: row for row in DATA['evidence']}
+            assert len(entries) == audit['recordCount'] == audit['readable']
+            assert audit['failed'] == 0 and len({e['candidateId'] for e in entries}) == len(entries)
+            years = Counter(str(e['foundedYear']) for e in entries)
+            assert dict(years) == audit['yearCounts']
+            for entry in entries:
+                row = candidates[entry['candidateId']]
+                proof = evidence_by_id[entry['evidenceId']]
+                assert row['profileStatus'] == 'readable' and proof['url'] == row['url']
+                assert entry['evidenceId'] in row['evidenceIds']
+                assert isinstance(entry['foundedYear'], int) and 1800 <= entry['foundedYear'] <= int(DATA['asOf'][:4])
+                assert isinstance(entry['teamSize'], int) and entry['teamSize'] >= 0
+                assert len(entry['htmlSha256']) == 64 and all(c in '0123456789abcdef' for c in entry['htmlSha256'])
+                if entry['foundedYear'] not in [2025, 2026]:
+                    assert row['status'] == 'outside-cohort' and not row.get('companyId')
+            assert sum(e['foundedYear'] not in [2025, 2026] for e in entries) == audit['outsideTargetYears']
+            assert sum(e['foundedYear'] in [2025, 2026] for e in entries) == audit['targetYearSelfReports']
+            assert sum(candidates[e['candidateId']]['status'] == 'linked' for e in entries) == audit['newLinkedCompanies']
+            assert sum(candidates[e['candidateId']]['status'] == 'pending-ai' for e in entries) == audit['pendingCurrentAIOrIdentity']
+            assert sum(candidates[e['candidateId']]['status'] == 'pending-year' for e in entries) == audit['pendingFoundingIdentity']
+            assert audit['targetYearSelfReports'] == (
+                audit['newLinkedCompanies'] + audit['pendingCurrentAIOrIdentity'] + audit['pendingFoundingIdentity']
+            ), 'self-reported years must retain unresolved brand/entity dates'
         if source['url']:
             assert urlsplit(source['url']).scheme in {'http', 'https'} and urlsplit(source['url']).netloc
         for host in source['hosts']:
@@ -49,7 +120,18 @@ def source_register():
         company_ids = {e['companyId'] for e in evidence if e['companyId']}
         observations = sum(o['evidence'] in evidence_ids for o in DATA['observations'])
         name = f"[{source['name']}]({source['url']})" if source['url'] else source['name']
-        lines.append(f"| {source['id']} {name} | {statuses[source['status']]} | {len(evidence)} / {len(company_ids)} / {observations} | {source['boundary']} | {source['nextCheck']} |")
+        boundary = source['boundary']
+        if source['id'] == 'S01':
+            summary = source['coverageSummary']
+            boundary += (f" 当前原候选池{summary['initialProfiles']}项，原新增{summary['originalImported']}项中"
+                         f"{summary['profileOnly']}项目录基础资料、{summary['deepenedOriginal']}项深化个案。")
+            for key, label in [('unclearAI', '原AI不明'), ('missingYear', '原缺年'), ('dateConflict', '原日期冲突')]:
+                group = summary[key]
+                labels = {'linked': '关联公司', 'pending-ai': 'AI主营待核',
+                          'pending-year': '成立/主体待核', 'outside-cohort': '范围外'}
+                counts = '、'.join(f'{labels.get(status, status)} {count}' for status, count in group['statuses'].items())
+                boundary += f" {label}{group['records']}项当前：{counts}。"
+        lines.append(f"| {source['id']} {name} | {statuses[source['status']]} | {len(evidence)} / {len(company_ids)} / {observations} | {boundary} | {source['nextCheck']} |")
     lines += ['', 'Dealroom、Product Hunt、机器之心与36氪入口于2026-10-30重新访问。官网首页可读不证明已取得完整筛选结果；安全检测页面不作为文章内容。候选池之外的来源边界尚需建立可回查条目，完成前不宣布来源清单已全部覆盖。', '']
     return lines
 
@@ -85,7 +167,7 @@ def candidate_register():
     all_ids = [r['id'] for b in batches for r in b['records']]
     assert len(set(all_ids)) == len(all_ids)
     lines = []
-    statuses = {'pending-year': '成立年待核', 'linked': '已关联公司',
+    statuses = {'pending-year': '成立年待核', 'pending-ai': 'AI主营待核', 'linked': '已关联公司',
                 'existing-outside-cohort': '已有关联，年份范围外',
                 'outside-cohort': '范围外或既有业务，不新增公司', 'promotion': '推广活动，非公司新增'}
     for batch in batches:
@@ -97,13 +179,13 @@ def candidate_register():
         assert sum(counts.values()) == len(rows)
         lines += ['', f"## {batch['sourceId']} 候选核对（{batch['id']}）", '',
             f"[发现页面]({batch['url']})，读取于{batch['accessedAt']}。{batch['scope']}", '',
-            f"本批{len(rows)}条：{counts['linked']}条关联公司、{counts['existing-outside-cohort']}条关联范围外对照、{counts['outside-cohort']}条范围外不新增公司、{counts['pending-year']}条成立年待核、{counts['promotion']}条推广活动。完整来源覆盖标记：{'已完成' if batch['complete'] else '未完成'}。主营或产品任务的初分类不计入主公司表数量，只有已关联的公司记录进入对应公司明细。候选与缺项随研究版本保存在文档站同一SQLite的研究元数据中。", '',
+            f"本批{len(rows)}条：{counts['linked']}条关联公司、{counts['existing-outside-cohort']}条关联范围外对照、{counts['outside-cohort']}条范围外不新增公司、{counts['pending-year']}条成立年待核、{counts['pending-ai']}条AI主营待核、{counts['promotion']}条推广活动。完整来源覆盖标记：{'已完成' if batch['complete'] else '未完成'}。主营或产品任务的初分类不计入主公司表数量，只有已关联的公司记录进入对应公司明细。候选与缺项随研究版本保存在文档站同一SQLite的研究元数据中。", '',
             '| 发现条目 | 主营或产品任务初分 | 核对状态 | 关联公司 | 核对证据 | 限制 |', '| --- | --- | --- | --- | --- | --- |']
         for row in rows:
             assert row['categoryId'] in categories
             assert row['status'] in statuses
             assert all(eid in evidence for eid in row.get('evidenceIds', []))
-            if row['status'] == 'outside-cohort':
+            if row['status'] in {'outside-cohort', 'pending-ai'}:
                 assert row.get('evidenceIds') and not row.get('companyId')
             name = f"[{row['name']}]({row['url']})" if row['url'] else row['name']
             company = '—'
@@ -121,6 +203,73 @@ def candidate_register():
     return lines
 
 
+def uncertain_ai_followups():
+    original = {row['source']: row for row in AUDIT['records'] if row['status'] == 'ai-unclear'}
+    rows = [row for batch in DATA.get('candidateBatches', [])
+            if batch['id'].startswith('YC-AI-UNCLEAR-') for row in batch['records']]
+    if not rows:
+        return []
+    urls = [row['url'] for row in rows]
+    assert len(set(urls)) == len(urls), 'Duplicate AI-relevance follow-up URL'
+    rechecks = {row['ycId']: row for row in DATA.get('directoryRechecks', [])}
+    counts = Counter(row['status'] for row in rows)
+    assert set(counts) <= {'linked', 'pending-ai'}
+    for row in rows:
+        assert row['url'] in original and row.get('evidenceIds')
+        baseline = original[row['url']]
+        if row['status'] == 'linked':
+            assert rechecks[baseline['ycId']]['companyId'] == row['companyId']
+        else:
+            assert not row.get('companyId') and baseline['ycId'] not in rechecks
+    unread = len(original) - len(rows)
+    assert unread >= 0
+    return ['', '## 原AI主营不明名单的后续覆盖', '',
+        f"原名单{len(original)}项，已有后续记录{len(rows)}项：{counts['linked']}项关联公司、{counts['pending-ai']}项仍待核AI主营，{unread}项尚无本批系列的后续记录。计数按原始YC页面去重；EveryApp此前的独立复核与末批记录不重复相加。", '',
+        '读完名单只证明每项有可回查的处理记录，不证明待核项均为AI公司，也不证明法律主体、收入或技术效果已独立验证。原始发现审计保持不变，成立年范围外/缺失、成立冲突及其他来源的缺项仍单列。', '']
+
+
+def founding_year_followups():
+    original = {row['source']: row for row in AUDIT['records'] if row['status'] == 'date-conflict'}
+    rows = [row for batch in DATA.get('candidateBatches', [])
+            if batch['id'].startswith('YC-DATE-CONFLICT-') for row in batch['records']]
+    urls = [row['url'] for row in rows]
+    assert len(set(urls)) == len(urls), 'Duplicate founding-conflict follow-up URL'
+    assert set(urls) <= set(original), 'Unknown founding-conflict follow-up URL'
+    evidence = {row['id']: row for row in DATA['evidence']}
+    for row in rows:
+        assert row['status'] == 'pending-year' and not row.get('companyId')
+        assert row.get('evidenceIds') and all(eid in evidence for eid in row['evidenceIds'])
+        assert all(evidence[eid]['companyId'] is None for eid in row['evidenceIds'])
+    unread = len(original) - len(rows)
+    return ['', '## 原成立年冲突名单的后续覆盖', '',
+        f"原名单{len(original)}项，已有后续记录{len(rows)}项，均保留成立年待核，{unread}项尚无本系列后续记录。当前业务初分类见候选表，不计入主公司表及收入统计。", '',
+        '2025旧品牌发布可证明当时已有产品材料；当前目录的2026字段、批次、条款日期和运营者名称不能单独证明法律主体成立或新旧主体连续。未据此强改成立年。Layers当前AI核心仍另待核。', '']
+
+
+def missing_year_followups():
+    original = {row['source'] for row in AUDIT['records']
+                if row['status'] == 'year-outside-or-missing' and row['foundedYear'] is None}
+    rows = [row for batch in DATA.get('candidateBatches', [])
+            if batch['id'].startswith('YC-MISSING-YEAR-') for row in batch['records']]
+    urls = [row['url'] for row in rows]
+    assert len(set(urls)) == len(urls) and set(urls) <= original
+    evidence = {e['id']: e for e in DATA['evidence']}
+    for row in rows:
+        assert row['status'] in {'outside-cohort', 'pending-year', 'pending-ai', 'linked'}
+        assert row.get('evidenceIds')
+        if row['status'] == 'linked':
+            matches = [r for r in DATA.get('directoryRechecks', []) if r['companyId'] == row.get('companyId')]
+            assert len(matches) == 1 and matches[0]['originalStatus'] == 'year-outside-or-missing'
+            assert all(eid in evidence and evidence[eid]['companyId'] == row['companyId'] for eid in row['evidenceIds'])
+        else:
+            assert not row.get('companyId')
+            assert all(eid in evidence and evidence[eid]['companyId'] is None for eid in row['evidenceIds'])
+    counts = Counter(row['status'] for row in rows)
+    return ['', '## 原缺少成立年名单的后续覆盖', '',
+        f"原快照缺年{len(original)}项，外部补核已有{len(rows)}项：{counts['linked']}项关联公司、{counts['outside-cohort']}项既有主体/业务范围外、{counts['pending-year']}项成立年待核、{counts['pending-ai']}项AI主营待核，{len(original)-len(rows)}项尚无本系列外部补核记录。", '',
+        '当前YC缺年字段复读与外部主体核查分别统计。登记创建日、公司自述年、产品发布、条款更新和批次不相互替代；已查英国或法国主体不代表完整集团沿革已核。原54项发现计数不回写，也不以Inactive补零收入。', '']
+
+
 def directory_rechecks():
     rows = DATA.get('directoryRechecks', [])
     if not rows:
@@ -167,6 +316,11 @@ def render():
         'year-outside-or-missing': cov['otherOrMissingYear'],
         'ai-unclear': cov['unclearAI'], 'date-conflict': cov['dateConflicts']}
     assert len({x['ycId'] for x in AUDIT['records']}) == len(AUDIT['records'])
+    excluded_years = Counter(x['foundedYear'] for x in AUDIT['records'] if x['status'] == 'year-outside-or-missing')
+    outside_years = {year: count for year, count in excluded_years.items() if year is not None}
+    assert all(year not in (2025, 2026) for year in outside_years)
+    assert sum(outside_years.values()) + excluded_years[None] == cov['otherOrMissingYear']
+    year_detail = '、'.join(f'{year}年{count}项' for year, count in sorted(outside_years.items()))
     lines = ['# AI 公司资料覆盖与缺项', '',
         f"截至 {DATA['asOf']}，研究表含{len(companies):,}条公司或产品记录。YC候选池有逐条读取审计；其他来源为定向补充。清单尚不能作为全球AI公司普查，也不能将收入未知解释为零。", '',
         '验收范围已于2026-10-30确认为：以确认的公开来源清单为边界，逐条核对并标明缺项。下方区分已逐条审计的候选池与定向补充来源；已使用某来源不代表该来源已被完整覆盖。', '',
@@ -178,7 +332,8 @@ def render():
         f"| 初筛匹配 | {cov['matchingProfiles']:,} | 成立年及AI相关描述通过初筛，尚非逐家商业验证 |",
         f"| 与原表重合 | {cov['existingProfiles']} | URL匹配，未再次新增 |",
         f"| 新增目录记录 | {cov['newProfiles']:,} | 原始入表来源，后续深化不改变发现计数 |",
-        f"| 年份不符或缺失 | {cov['otherOrMissingYear']} | 此轮不作为成立年匹配项 |",
+        f"| 原目录列为范围外年份 | {sum(outside_years.values())} | {year_detail}；原快照自述，不是独立登记核验 |",
+        f"| 原目录未给成立年 | {excluded_years[None]} | 与已列范围外年份分开，仍待补证 |",
         f"| AI业务待确认 | {cov['unclearAI']} | 不强行把背景关键词当主营 |",
         f"| 成立年与批次冲突 | {cov['dateConflicts']} | 另保留核查记录 |", '',
         f"全表由{depth}条目录基础项和{len(companies)-depth}条个案或平台记录组成。候选池已匹配项之外另有{len(companies)-cov['matchingProfiles']}条记录，包含其他来源及发布/转型对照；其中已有{promoted}条原目录记录深化为个案，仍保留目录来源。两种统计边界不同。候选池数字只是该镜像快照的覆盖，Bud等后续定向补充不回填为原候选池已覆盖。", '',
@@ -217,13 +372,16 @@ def render():
         lines.append(f"| {name} | {len(entries)} | {len({e['url'] for e in entries})} | {note} |")
     others = [e for e in DATA['evidence'] if urlsplit(e['url']).netloc not in included]
     lines.append(f"| 其他官网、评测及公开资料 | {len(others)} | {len({e['url'] for e in others})} | 按每条来源限制理解，不能统一当作独立证据 |")
+    lines += uncertain_ai_followups()
+    lines += founding_year_followups()
+    lines += missing_year_followups()
     lines += directory_rechecks()
     lines += source_register()
     lines += context_methods()
     lines += candidate_register()
     lines += ['', '## 尚未满足的研究条件', '',
         '行业ARR比较仍缺统一业务截止日、币种、经常性定义和业务边界。现有平台MRR可描述已采集产品，不足以代表全部新公司。技术评测只覆盖所列版本与任务，不宜跨领域汇总为统一强弱分数。', '',
-        '下一轮优先补收入线索的日期及合同定义、非YC和非英文来源、规则初分的人工复核，以及停止服务或被收购案例。这样能减少“只见赢家”和“只见融资公司”的偏差。公开来源池之外的未披露公司仍无法证明已被穷尽。', '',
+        '下一轮优先补收入线索的日期及合同定义、成立年冲突、AI主营仍待核项、非YC和非英文来源，以及停止服务或被收购案例。这样能减少“只见赢家”和“只见融资公司”的偏差。公开来源池之外的未披露公司仍无法证明已被穷尽。', '',
     ]
     return '\n'.join(lines)