feat: explain income dispersion within comparable sample groups

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>)}