[verified] Declarative factor engine + per-symbol stock selection (full-app consistency)
- factors.py: FACTORS registry (10 declarative entries: source/fetch/frequency/sign/weight) + normalize/z-score helpers. Add a source = one dict entry, no scoring-function edit.
- themes.THEMES: 13 themes reference FACTORS with per-theme weights (flexible), replacing hardcoded _theme_surprises/_theme_narrative.
- themes.quality_within_theme(): per-symbol quality vs theme cohort (ROE/EPS) -> real stock picking. dashboard board now surprise×quality (BBL 0.5 vs KTB 1.5 in banks).
- board rows carry per-symbol themes[]; /api/v1/themes delegates to RealDashboard.build() -> 13-theme consistency with /api/v1/dashboard (removed 115 lines dead dup logic).
- frontend: deleted THEME_BY_SYMBOL/themeLabelById hardcode; theme column + modal labels+quality all from API. Modal shows surprise×quality=theme_score.
- Tests: 202 OK (quality selection, breakdown quality, themes/dashboard consistency).
- Verified: BBL modal 1.00σ×0.5=0.50σ; KTB 1.5 vs BBL 0.5, PTT 2 themes; 49/49 rows theme from API.
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