Site tier-1 follow-up: per-model deep-dive page

[MaxGhenis]

Summary

Follow-up to #8 and #9. Adds a statically-generated per-model deep-dive page at /model/[id] — one page per model present in data.json.

Rendered sections

1. Headline strip (inside SiteHeader expandedContent, alwaysExpanded)

• Provider mark (ProviderMark) + model name + provider label
• Score pills: Global, US, UK (from globalStat.countryScores), Parse rate (nParsed / n)

2. Hardest outputs — top 5 lowest-scoring output groups for this model

• Aggregated at (country, outputGroup) level using buildAllRows + scorePrediction from lib/sensitivity.ts / lib/scoring.ts
• The aggregation mirrors the 3-level mean in scoresPerCountryModel: per-row scores → output-group mean → displayed score
• Shows variable label (getVariableLabel), country tag, and a Badge (same color thresholds as ModelLeaderboard)

3. Sample wrong predictions — up to 10 distinct (country, scenario, variable) cells where relErr > 10% and score < 0.75

• Sorted by largest relative error first
• Each card: country tag, variable label, score badge, Prediction / Ground truth / Error columns (currency-formatted for amount outputs, integer for binary)
• Collapsible <details> block with the model's explanation text
• Link to /#scenarios for the scenario explorer, plus the scenario ID

4. Back to leaderboard link at page bottom

Static routes generation

generateStaticParams collects all model IDs from dashboard.global.modelStats and the union of country-level modelStats, returning one { id } entry per model. The current data produces 12 static routes:

/model/gpt-5.5
/model/claude-sonnet-4.6
/model/claude-opus-4.7
/model/grok-4.20
/model/gemini-3.1-pro-preview
/model/gemini-3-flash-preview
/model/grok-4.3
/model/gemini-3.1-flash-lite-preview
/model/gpt-5.4-mini
/model/grok-4.1-fast
/model/claude-haiku-4.5
/model/gpt-5.4-nano

Library reuse

Library	Used for
lib/scoring.ts — scorePrediction, metricTypeForVariable	Per-row score computation, metric type for display formatting
lib/sensitivity.ts — buildAllRows	Builds the full ScoreRow[] for all countries, filtered to the model
lib/bootstrap.ts	Not needed for static server render; omitted

Scoring math

For each (country, outputGroup) pair, the displayed score is the mean of per-row scores (each scorePrediction result × 100) across all scenarios and person-expanded variables that map to that output group. This is equivalent to the inner two levels of the 3-level mean in scoresPerCountryModel.

Smoke test

bun run lint   # clean (0 errors, 0 warnings)
bun run build  # clean — /model/[id] SSG route with 12 paths in build output

Build output excerpt:

● /model/[id]
│ ├ /model/gpt-5.5
│ ├ /model/claude-sonnet-4.6
│ ├ /model/claude-opus-4.7
│ └ [+9 more paths]

Test plan

• CI passes
• Visit /model/gpt-5.5 — headline shows Global / US / UK scores, parse rate
• Verify "Top 5 lowest-scoring outputs" renders 5 rows with country tags and score badges
• Verify "Sample errors" section renders cards with prediction / ground truth / error
• Expand a model explanation <details> block
• Click "View in scenario explorer →" — lands on /#scenarios
• Click "← Back to leaderboard" — returns to /
• Visit /model/nonexistent-model — returns 404
• Mobile width — score pills wrap cleanly under provider mark

🤖 Generated with Claude Code

Scheduled follow-up agent — opened after confirming both #8 and #9 are merged.

---

Generated by Claude Code

[vercel]

The latest updates on your projects. Learn more about Vercel for GitHub.

Project	Deployment	Actions	Updated (UTC)
policybench-site	Ready	Preview, Comment	May 16, 2026 1:11pm