feat(P4): IHF Phase 4 complete — Outcome Observation and Antifragility Loop

Closes the IHF improvement loop. Full antifragility chain now traversable:
Widget → Annotation → Candidate → Requirement → Decision → Deployment → OutcomeSignal

New artifacts:
- DeploymentRecord (immutable, links DecisionRecord to a deployed version)
- OutcomeSignal (append-only; DB trigger prevents UPDATE/DELETE)
- ChangeEvaluation (one-per-deployment; UNIQUE constraint; 1–5 score)

New capabilities:
- DeploymentRecordsController (index, show, new, create)
- RecordOutcomeSignalAction — capture improved/regressed/neutral/inconclusive signals
- Pre/post comparison panel on deployment show (±30-day event/annotation counts)
- Regression detection — improved signal followed by high/critical annotation
- ChangeEvaluation — idempotent score+rationale per deployment
- Recurrence tracking — cycle count per widget, leaderboard
- AntifragilityDashboardAction (autoRefresh, 5 panels) per hub
- Phase 4 integration tests (T01–T08 logic coverage)
- docs/phase4-summary.md; SCOPE.md updated to Phase 4 complete

State Hub: workstream 07e9c860 → completed

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

docs/phase4-summary.md

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+# Phase 4 Summary — Outcome Observation and Antifragility Loop
+
+**Workplan:** IHUB-WP-0004
+**Completed:** 2026-03-29
+**Phase:** 4 of 8 in the IHF specification
+
+---
+
+## What Was Built
+
+Phase 4 closes the IHF improvement loop by connecting deployed versions to observed outcomes. The full chain is now traversable:
+
+```
+Widget → InteractionEvent / Annotation
+       → RequirementCandidate → Requirement
+       → DecisionRecord → ImplementationChangeReference
+       → DeploymentRecord
+       → OutcomeSignal  ←  ChangeEvaluation
+       → RegressionDetection / RecurrenceTracking
+```
+
+### T01 — Schema
+
+Three new tables:
+- **`deployment_records`** — immutable link from a decision to a deployed version (`version_ref`, `deployed_at`, `deployed_by`, `notes`)
+- **`outcome_signals`** — append-only observations of widget behaviour post-deployment (`signal_type`, `value`, `observed_at`); PostgreSQL trigger prevents UPDATE/DELETE
+- **`change_evaluations`** — one score (1–5) per deployment with rationale; UNIQUE constraint on `deployment_id`
+
+### T02 — DeploymentRecords Controller and Views
+
+`DeploymentRecordsController` with index, show, new, create (no update/delete — immutable by convention). Decision show page includes a "New Deployment" button (gated on having at least one implementation reference). Deployment show page renders the full decision chain: Decision → ImplRef → Requirement → Candidate → Widget.
+
+### T03 — OutcomeSignal Capture
+
+`RecordOutcomeSignalAction` (POST from deployment show page). Signal types: `improved`, `regressed`, `neutral`, `inconclusive` with color coding (green/red/gray/yellow). Widget show page lists the last 10 signals across all deployments.
+
+### T04 — Pre/Post Comparison
+
+Comparison panel on the deployment show page. Computes interaction event counts and annotation severity distribution for the 30-day window before vs. after `deployed_at`. Delta column: green if annotation rate decreased, red if increased. Works with no post-deployment data (shows "—").
+
+### T05 — Regression Detection
+
+`regressedWidgetIds` pure function in `Application.Helper.Controller`. A regression is: any widget with an `OutcomeSignal(improved)` followed (> 1 day later) by a new `Annotation(severity=high|critical)`. Regression badge on widget show page; regression count and widget list on governance dashboard; prominent alerts panel on antifragility dashboard.
+
+### T06 — ChangeEvaluation
+
+`EvaluateChangeAction` (POST). Idempotent — second attempt on same deployment redirects with "Already evaluated" message. Score 1–5 rendered as ★ stars with color (1–2 red, 3 yellow, 4–5 green). Evaluation summary shown on decision show page alongside each deployment row.
+
+### T07 — Recurrence Tracking
+
+`widgetCycleCounts` function computes completed improvement cycles per widget (cycle = accepted candidate → requirement → decision → deployment → new candidate). Cycle count badge ("⟳ N cycles") on widget show page for cycle_count ≥ 2. Top-10 leaderboard on antifragility dashboard.
+
+### T08 — Antifragility Dashboard
+
+`AntifragilityDashboardAction` wrapped with `autoRefresh do`. Five panels:
+1. **KPI row**: total deployments / avg evaluation score / % improved signals / regression count
+2. **Regression alerts**: widgets currently in regression (red panel, links to widget show pages)
+3. **Open gaps**: decisions with impl refs but no deployment record yet
+4. **Recent deployments** (last 20): version ref, decision title, signal dots, evaluation score
+5. **Recurrence leaderboard**: top 10 widgets by cycle count
+
+Linked from hub show page (green "Antifragility" button) and governance dashboard.
+
+---
+
+## Known Limitations
+
+- **Pre/post comparison uses Haskell-side filtering**, not SQL aggregates. For production use with large datasets, replace `computeComparison` with `[typedSql|...|]` queries (IHP v1.5 typed quasiquoter).
+- **Regression detection is a heuristic**. It detects any high/critical annotation after an improved signal — it does not distinguish whether the annotation relates to the same aspect of the widget that was improved.
+- **Cycle count requires a strict data chain**. Cycles are only counted when the full candidate→requirement→decision→deployment chain exists. Partial cycles (e.g., a decision without a deployment) are not counted.
+- **No ML in Phase 4**. All scoring and detection is rule-based. Agent-assisted distillation begins in Phase 5.
+
+---
+
+## Phase 5 Readiness
+
+Phase 5 (Agent-Assisted Distillation) can now build on:
+- `OutcomeSignal` as evidence input for agent distillation
+- `ChangeEvaluation` scores as feedback signal for agent learning
+- `RegressionDetection` results as priority signal for agent attention
+- The full traceability chain from widget to outcome is traversable in one hop