feat(WP-0013): IHF Phase 12 — Platform Memory and Continuous Learning

Closes the long-range feedback loop: outcome signals now enrich the full
traceability chain and feed back into routing, triage, and AI proposals.

Schema (T01):
- outcome_correlations (CHECK correlation_type)
- pattern_performance_records
- adaptive_threshold_configs
- institutional_knowledge_entries (GIN tsvector FTS)
- learning_insights (CHECK insight_type)
- ALTER TABLE decision_records + requirement_candidates: outcome_summary JSONB
- AFTER INSERT trigger trg_enrich_lineage on outcome_signals
- contracts/core/ updated (outcome-summary-columns-v1, append-only addendum)

Correlation engine (T02):
- Application/Helper/CorrelationEngine.hs: pure annotation→outcome SQL
- Web/Controller/OutcomeCorrelations.hs: ComputeCorrelationsAction + index

Pattern performance (T03):
- Web/Controller/PatternPerformance.hs: ComputePatternPerformanceAction

Adaptive thresholds (T04):
- Web/Controller/AdaptiveThresholds.hs: CalibrateThresholdsAction
- Application/Helper/FrictionScore.hs: applyAdaptiveWeights

Institutional knowledge (T05):
- DistilDecisionAction in DecisionRecords controller
- Web/Controller/InstitutionalKnowledge.hs: QueryKnowledgeBaseAction

Lineage enrichment (T06):
- Web/Controller/LineageEnrichment.hs: EnrichLineageAction (batch backfill)
- enrich_lineage_on_outcome_batch() PL/pgSQL helper in migration

Learning dashboard (T07):
- Web/Controller/LearningDashboard.hs: 5-panel autoRefresh view
- "Learning" nav link in FrontController

API v2 learning endpoints (T08):
- GET /api/v2/outcome-correlations, /pattern-performance, /knowledge-base/{id}
- OpenAPI schemas: OutcomeCorrelation, PatternPerformanceRecord, InstitutionalKnowledgeEntry

GAAF scorecard + docs (T09):
- Core 3.8→3.9, Functional 3.6→3.8, overall 3.61→3.68
- CLAUDE.md: IHF v0.2 complete, no active workplan

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

Web/Controller/OutcomeCorrelations.hs

@@ -0,0 +1,58 @@
+module Web.Controller.OutcomeCorrelations where
+
+-- IHF Phase 12 — Platform Memory (IHUB-WP-0013 T02)
+
+import Web.Controller.Prelude
+import Web.View.OutcomeCorrelations.Index
+import Application.Helper.CorrelationEngine (computeAnnotationCorrelations)
+import Data.Aeson ((.=), object)
+
+instance Controller OutcomeCorrelationsController where
+    beforeAction = ensureIsUser
+
+    action OutcomeCorrelationsAction = do
+        mHubFilter <- paramOrNothing @(Id Hub) "hubId"
+        correlations <- case mHubFilter of
+            Nothing -> query @OutcomeCorrelation
+                |> orderByDesc #correlationScore
+                |> fetch
+            Just hid -> query @OutcomeCorrelation
+                |> filterWhere (#hubId, hid)
+                |> orderByDesc #correlationScore
+                |> fetch
+        hubs <- query @Hub |> orderByAsc #name |> fetch
+        render IndexView { correlations, hubs, mHubFilter }
+
+    action ComputeCorrelationsAction { hubId } = do
+        rows <- liftIO $ computeAnnotationCorrelations hubId
+        now  <- getCurrentTime
+        -- Upsert: delete existing rows for this hub then insert fresh
+        deleteWhere @OutcomeCorrelation (#hubId, hubId)
+        forM_ rows \(category, score, sampleCount) ->
+            newRecord @OutcomeCorrelation
+                |> set #hubId hubId
+                |> set #annotationCategory category
+                |> set #correlationType "annotation_predictor"
+                |> set #correlationScore score
+                |> set #sampleCount sampleCount
+                |> set #computedAt now
+                |> createRecord
+
+        -- Generate LearningInsight for top-scoring category
+        case rows of
+            ((topCat, topScore, _) : _) | topScore >= 0.4 ->
+                newRecord @LearningInsight
+                    |> set #hubId hubId
+                    |> set #insightType "annotation_predictor"
+                    |> set #title ("Strong predictor: annotation category '" <> topCat <> "'")
+                    |> set #body ("Annotation category '" <> topCat <> "' shows a correlation score of "
+                        <> show topScore <> " with positive outcomes. Consider weighting this category "
+                        <> "higher in triage and routing decisions.")
+                    |> set #evidenceLinks (A.toJSON
+                        [object ["type" .= ("outcome_correlation" :: Text), "category" .= topCat]])
+                    |> createRecord
+                >> pure ()
+            _ -> pure ()
+
+        setSuccessMessage ("Correlations computed: " <> show (length rows) <> " categories")
+        redirectTo OutcomeCorrelationsAction