Quest: Gap Factory Priority: P2 Status: open
Add gap prioritization scoring based on research impact potential
This task is part of the Gap Factory quest (Atlas layer). It contributes to the broader goal of building out SciDEX's atlas capabilities.
gap_scoring.py (scidex/agora/gap_scoring.py) already exists and implements 5-dimension research impact scoring via LLM (importance, tractability, hypothesis_impact, novelty, data_readiness) using compute_gap_score() from scidex/exchange/exchange.py. The gap_quality.py separately handles gap quality dimensions (specificity, evidence_coverage, hypothesis_density, debate_depth, actionability).gap_scoring.score_knowledge_gap() to filter auto-detected gaps by importance_score >= 0.5 before creating./api/gaps GET endpoint sorts by priority_score and already returns gaps with composite/priority scores. No POST endpoint existed to trigger re-scoring on demand.POST /api/gaps/{gap_id}/score endpoint (api.py lines ~8386) that:gap_scoring.score_knowledge_gap() for LLM evaluationupdate_knowledge_gap()7fbc8d979 [Atlas] Add POST /api/gaps/{gap_id}/score (api.py) — gap research impact scoring endpoint{
"_reset_note": "This task was reset after a database incident on 2026-04-17.\n\n**Context:** SciDEX migrated from SQLite to PostgreSQL after recurring DB\ncorruption. Some work done during Apr 16-17 may have been lost.\n\n**Before starting work:**\n1. Check if the task's goal is ALREADY satisfied (run the relevant checks)\n2. Check `git log --all --grep=task:YOUR_TASK_ID` for prior commits\n3. If complete, verify and mark done. If partial, continue. If not done, proceed.\n\n**DB change:** SciDEX now uses PostgreSQL. `get_db()` auto-detects via\nSCIDEX_DB_BACKEND=postgres env var.",
"_reset_at": "2026-04-18T06:29:22.046013+00:00",
"_reset_from_status": "done"
}