Keep income statistics columns readable with grouped rows

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, 1039);
+  assert.equal(research.companies.length, 1029);
   assert.equal(research.categories.length, 11);
-  assert.equal(research.evidence.length, 1445);
-  assert.equal(research.observations.length, 202);
+  assert.equal(research.evidence.length, 1412);
+  assert.equal(research.observations.length, 192);
   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/IncomeDistribution.tsx

@@ -75,7 +75,7 @@ export default function IncomeDistribution({ data, onSelect }: {
         </svg></div>
         <figcaption>圆点：产品观测　竖线：样本均值　菱形：样本中位数。业务类别标题下各行按支付平台{splitModels && "及收费与交付模式"}分别统计；n为该组产品数。点击点或下表产品名可看原始证据。</figcaption>
       </figure>
-      <div className="research-table-wrap"><table><caption>{metric}样本统计；每行是类别下的一个统计组，CV使用样本标准差</caption><thead><tr><th scope="col">业务类别</th><th scope="col">支付平台 / 收费模式</th><th scope="col">n</th><th scope="col">均值</th><th scope="col">中位数</th><th scope="col">均值/中位数</th><th scope="col">CV</th><th scope="col">去除最大值后的均值 / 下降幅度</th><th scope="col">产品与限制</th></tr></thead>{categoryGroups.map(({ category, rows }) => <tbody key={category}>{rows.map((group, index) => <tr key={group.key}>
+      <div className="research-table-wrap"><table className="income-statistics"><caption>{metric}样本统计；每行是类别下的一个统计组，CV使用样本标准差</caption><thead><tr><th scope="col">业务类别</th><th scope="col">支付平台 / 收费模式</th><th scope="col">n</th><th scope="col">均值</th><th scope="col">中位数</th><th scope="col">均值/中位数</th><th scope="col">CV</th><th scope="col">去除最大值后的均值 / 下降幅度</th><th scope="col">产品与限制</th></tr></thead>{categoryGroups.map(({ category, rows }) => <tbody key={category}>{rows.map((group, index) => <tr key={group.key}>
         {index === 0 && <th scope="rowgroup" rowSpan={rows.length}>{categories.get(category)}<small>{rows.length}个统计组</small></th>}
         <td>{group.provider}<small>{group.model}</small></td><td>{group.stats.n}</td><td>{usd(group.stats.mean)}</td><td>{usd(group.stats.median)}</td><td>{group.stats.meanMedianRatio?.toFixed(2) ?? "—"}</td><td>{group.stats.cv?.toFixed(2) ?? "—"}</td><td>{usd(group.stats.meanWithoutLargest)}<small>{percent(group.stats.largestRemovalDrop)}</small></td>
         <td>{group.points.map((point) => <span key={point.company.id}><button className="research-company-name" onClick={() => onSelect(point.company.id)}>{point.company.name}</button>{" "}</span>)}<small>{group.stats.n < 3 ? "样本少于3，不能据此判断领域典型收入。" : "自选的小样本，须结合产品年龄、成本与留存评估。"}</small></td>

apps/docs/src/styles/globals.css

@@ -1473,6 +1473,13 @@ svg { flex-shrink: 0; }
 
 .research-distribution { margin: 24px 0 38px; }
 .research-distribution figure { margin: 20px 0; }
+.ai-research .income-statistics { min-width: 1200px; }
+/* Row-spanning category headings shift cell indexes between rows. */
+.ai-research .income-statistics td { min-width: 0; }
+.ai-research .income-statistics th[scope="rowgroup"] { min-width: 150px; white-space: nowrap; }
+.ai-research .income-statistics th[scope="rowgroup"] small { display: block; margin-top: 5px; }
+.ai-research .income-statistics td:not(:last-child) { white-space: nowrap; }
+.ai-research .income-statistics td:last-child { min-width: 220px; }
 .income-distribution-chart { display: block; width: 100%; min-width: 900px; height: auto; }
 .income-distribution-chart [role="button"] { cursor: pointer; outline: none; }
 .income-distribution-chart [role="button"]:focus circle:last-child { stroke: #b17725; stroke-width: 3; }

apps/docs/tests/research.test.ts

@@ -23,9 +23,9 @@ 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, 1039);
-    assert.equal(initial.evidence.length, 1445);
-    assert.equal(initial.observations.length, 202);
+    assert.equal(initial.companies.length, 1029);
+    assert.equal(initial.evidence.length, 1412);
+    assert.equal(initial.observations.length, 192);
     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 +64,9 @@ 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, 85);
+  assert.equal(snapshot.reviews.filter((r) => r.scope === "companies").length, 74);
   assert.equal(snapshot.reviews.filter((r) => r.scope === "dataset").length, 10);
-  assert.equal(snapshot.reviews.filter((r) => r.scope === "excluded-candidate").length, 38);
+  assert.equal(snapshot.reviews.filter((r) => r.scope === "excluded-candidate").length, 37);
   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 +85,11 @@ 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), 1039);
-  assert.equal(summary.reduce((n, c) => n + c.self, 0), 32);
+  assert.equal(summary.reduce((n, c) => n + c.count, 0), 1029);
+  assert.equal(summary.reduce((n, c) => n + c.self, 0), 28);
   assert.equal(summary.reduce((n, c) => n + c.estimate, 0), 2);
   assert.equal(summary.reduce((n, c) => n + c.platform, 0), 16);
-  assert.equal(summary.reduce((n, c) => n + c.unknown, 0), 989);
+  assert.equal(summary.reduce((n, c) => n + c.unknown, 0), 983);
   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"));
@@ -97,8 +97,8 @@ test("disclosure counts exclude client income, biographies, targets and duplicat
 
 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, 38);
-  assert.equal(snapshot.companies.filter((c) => c.technicalReview?.level === "public-artifact").length, 8);
+  assert.equal(snapshot.companies.filter((c) => c.technicalReview).length, 28);
+  assert.equal(snapshot.companies.filter((c) => c.technicalReview?.level === "public-artifact").length, 7);
   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/);
@@ -307,7 +307,7 @@ 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, 13);
+  assert.equal(snapshot.candidateBatches!.flatMap((b) => b.records).filter((r) => r.status === "pending-year").length, 10);
 });
 
 test("product pivots and founder histories do not become new company years or current revenue", () => {

content/research/ai-companies.sources.json

@@ -1,5 +1,5 @@
 {
-  "version": "2026-10-30-31",
+  "version": "2026-10-30-29",
   "scopeConfirmedAt": "2026-10-30",
   "acceptance": "以确认的公开来源清单为边界，逐条核对并标明缺项。",
   "provenance": "S01—S12恢复自已提交用户的《AI公司研究_来源与分类模板》来源清单；S13—S16单列后续已使用的补充证据渠道，不将使用次数当作全量覆盖。",
@@ -221,8 +221,8 @@
         "eu.36kr.com"
       ],
       "initialAccess": "安全检测，内容未核验",
-      "boundary": "此前首页安全检测仍保留；本轮4项定向检索及相关段落补查，3项据政府/公司/交易当事方资料关联、1项按原始登记归范围外。清析检索与直达正文不一致未确认关联，其他文章为平台发布/授权转载，不代表两年全量。 另登记合木、昆腾动力、寰宇心生3项报道相关段落，原始成立/主体留缺，未新增主公司表；不是全量。",
-      "nextCheck": "墨甲已由交易当事方原始公告补足2025成立及历史期间收入，母公司项目沿革和当前财务仍待核；继续补清析发现文章关联及未读正文，建两年公开文章台账，不绕过访问保护。 补本组三项公司/孵化/投资原始资料，避免融资与研究院、母体业绩归属混淆。",
+      "boundary": "此前首页安全检测仍保留；本轮4项定向检索及相关段落补查，3项据政府/公司/交易当事方资料关联、1项按原始登记归范围外。清析检索与直达正文不一致未确认关联，其他文章为平台发布/授权转载，不代表两年全量。",
+      "nextCheck": "墨甲已由交易当事方原始公告补足2025成立及历史期间收入，母公司项目沿革和当前财务仍待核；继续补清析发现文章关联及未读正文，建两年公开文章台账，不绕过访问保护。",
       "limitation": "仅核具体相关段落，检索和直达差异、转载与原始披露分别记录。",
       "accessRecheckedAt": "2026-10-30"
     },
@@ -234,7 +234,7 @@
       "status": "per-company",
       "hosts": [],
       "initialAccess": "按公司逐一核验",
-      "boundary": "公司官网和官方材料逐条绑定证据；不是可预先列尽的全站候选池。 定向新增企智芯与九昇智能的2025成立自述及交付资料，精确注册、实际客户与收入未核；两个官网不代表中文公司全集。",
+      "boundary": "公司官网和官方材料逐条绑定证据；不是可预先列尽的全站候选池。",
       "nextCheck": "核定价、主体、交付与收入定义，自述与独立验证分开。",
       "limitation": "自述不等于独立审计"
     },
@@ -262,8 +262,8 @@
         "speedrun.a16z.com"
       ],
       "initialAccess": "见具体证据访问记录",
-      "boundary": "投资机构公司介绍定向样本，收入数字仍多来自公司。 新增8项2026名录定向核查并登记候选台账（7项SR007、Bota SR006），不等全部批次或两年目录。",
-      "nextCheck": "核币种、相对时间及管线/履历；未读取的页面保持缺项。 区分live ARR、signed/contracted ARR、固定法律承诺费用、管线、目标交易量及客户收益；Nexor原$不自动当USD，财务日历截至日和合同底表留缺。",
+      "boundary": "投资机构公司介绍定向样本，收入数字仍多来自公司。",
+      "nextCheck": "核币种、相对时间及管线/履历；未读取的页面保持缺项。",
       "limitation": "来源可读不等于声明已独立验证。"
     },
     {

content/research/ai-income-analysis.json

@@ -1,5 +1,5 @@
 {
-  "sourceVersion": "2026-10-30-speedrun-contracts-1",
+  "sourceVersion": "2026-10-30-tc-p56-1",
   "asOf": "2026-10-30",
   "metric": "platform-mrr-usd",
   "sampleUnit": "product-or-business",