Add paper ingestion quality gate - #610
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/claim #13
Summary
Adds
paper-ingestion-quality-gate, a focused intake guard for the AI Paper Summarizer in SCIBASE's AI-Assisted Research Tools MVP. It checks whether an uploaded or repository-linked paper has been extracted cleanly enough before the summarizer generates key findings, implications, or next steps.This is intentionally narrow: it does not score the generated summary, validate citation context, check journal venue quality, assess statistics, run reporting guidelines, detect plagiarism, review disclosures, or audit figure/table claim support. It sits earlier in the workflow: before summarization, when broken PDF/OCR/table/reference extraction can quietly poison downstream AI output.
What It Covers
Included Artifacts
paper-ingestion-quality-gate/src/index.jspaper-ingestion-quality-gate/data/sample_ingestion_packets.jsonpaper-ingestion-quality-gate/test/paper-ingestion-quality-gate.test.jspaper-ingestion-quality-gate/scripts/demo.jspaper-ingestion-quality-gate/reports/Validation
npm.cmd test: 8 tests passed.npm.cmd run check: syntax checks passed.npm.cmd run demo: generated 4-packet report withSUMMARIZE: 1,REVIEW: 1,HOLD: 2.npm.cmd run video: generatedreports/demo.mp4.git diff --check: passed.ffprobe: H.264, 1280x720, 8.000 seconds, 30 fps, 240 frames.The MP4 is a generated FFmpeg color-source/drawtext slate, not a desktop or browser recording. It contains no private data.