GPT-5.5 Review Identified Five Critical Infrastructure Gaps in Original Plan
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obs· Harvested: 2026-05-02 · Original date: 2026-05-02T01:48:45.909Z Metadata:{"project":"lunhsiangyuan","type":"discovery","obs_id":64890}
obs/64890 · discovery · 2026-05-02T01:48:45.909Z
GPT-5.5 Review Identified Five Critical Infrastructure Gaps in Original Plan
GPT-5.5 high-level review (via cursor agent CLI) returned REVISE verdict identifying systematic gaps in original incremental load plan. Query coverage analysis revealed nomenclature diversity causing trial omission: bispecific trials may be labeled as “BiTE”, “T-cell engager”, “CD3 bispecific”, or “dual-targeting antibody”; ADC Phase 2/3 trials often use only commercial/INN names without “ADC” keyword. Review traced critical phase_group backfill omission: load_trials_from_json() INSERT logic does not call classify_phase_group(), leaving new trials with NULL phase_group values that cause mechanism tagging queries to miss Phase 2/3 trials entirely. Workflow analysis identified batch_mechanism_tag.py only generates CSV output with “rerun migration” prompt, incompatible with incremental load approach requiring direct database writes via apply_mechanism_overrides.py. Loop timing assessment found online research rounds (Phase 3 deep-dive, target pair analysis, competitive landscape) cannot complete quality analysis within 3-minute intervals. Deduplication gap confirmed: while single ClinicalTrials.gov query typically returns unique NCT IDs, custom_query path lacks built-in deduplication and cross-query overlap certain with 12-query strategy, requiring explicit merge step before database load for accurate trial counts in final report. All five issues addressed in revised plan with expanded query arrays, etl/merge_supplement_json.py step, phase_group backfill integration, apply_mechanism_overrides.py usage, and adjusted loop timing.
Concepts: [“gotcha”,“problem-solution”,“trade-off”]
Facts: [“Single-query approach insufficient: “bispecific antibody” misses BiTE/T-cell engager/dual-targeting variants; “antibody drug conjugate” misses Phase 2/3 trials using only trade names without ADC nomenclature”,“load_trials_from_json() does not populate phase_group column on INSERT, breaking downstream batch_mechanism_tag.py queries that depend on trial.phase_group for Phase 2/3 classification”,“batch_mechanism_tag.py outputs only overrides CSV and prompts migration rebuild; incremental load requires separate apply_mechanism_overrides.py execution to write mechanism tags to database”,“Original 8 rounds × 3 minutes timing too tight for online research rounds (R2/R4/R7); DB-only rounds acceptable at 3 minutes but online rounds need 5-8 minutes”,“Custom query path bypasses phase filter but also lacks deduplication; cross-query overlap guaranteed, requiring explicit JSON merge step for interpretable trial counts in report”]
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