๐ŸŒ™ SinkAlert Overnight Research

Babigon (91 data sources) ร— Ginnie (19 papers, 24 tools) ร— 4 rounds each
Full synthesis + brutal critique โ€” all files viewable & downloadable

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Research Files
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8h
Research Time
Synthesis Final Reports
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SINKALERT_OVERNIGHT_CRITIQUE.md
17 KB ยท 407 lines ยท Jun 29, 2026
CRITICAL READ. Ginnie's brutal verdict (5.5/10 โ€” NOT READY). Cross-examination of every claim, contradictions with Babigon, 10 judge questions, Week 1 fix plan (+17 points).
โฌ‡ Download GitHub
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SINKALERT_OVERNIGHT_SYNTHESIS.md
16 KB ยท 291 lines ยท Jun 29, 2026
Babigon's unified synthesis: Top 10 data sources, Top 10 papers/tools, 4-phase integration roadmap (260 hrs), pitch deck recommendations, SWOT analysis.
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Babigon Global Data Hunt โ€” 4 Rounds
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babigon_r1_data.md
18 KB ยท 471 lines
Round 1: 91 potential data sources discovered โ€” open + paid + academic. Cast the widest net across Zenodo, NASA, ESA, USGS, BGS, commercial satellites, insurance databases, Thai government portals.
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babigon_r2_ranked.md
18 KB ยท 444 lines
Round 2: Top 20 verified โ€” URLs tested, data schemas inspected. Ranked by composite score (accessibility + predictive value + cost). All top 10 are FREE.
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babigon_r3_deep.md
15 KB ยท 391 lines
Round 3: Deep dive on top 5 sources. Actual data fields, feature mapping to SinkAlert, F1 gain estimates, sample queries, integration pseudocode.
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babigon_r4_integration.md
13 KB ยท 342 lines
Round 4: Step-by-step integration order. Cost breakdown (everything free for research). Time estimates. Expected F1 improvement per source (+0.02-0.08 each).
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Ginnie Academic & Code Deep Research โ€” 4 Rounds
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ginnie_r1_papers.md
13 KB ยท 268 lines
Round 1: 19 key papers with DOIs. Sinkhole prediction, InSAR+ML, pavement CV, groundwater-subsidence, karst mapping, physics-informed NN, graph neural networks, foundation models.
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ginnie_r2_code.md
13 KB ยท 300 lines
Round 2: 24 production-ready tools. GitHub repos (stars, activity, license), HuggingFace models, QGIS plugins, SAR processors. Includes qgis-mcp (161โ˜…) evaluation.
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ginnie_r3_benchmark.md
10 KB ยท 244 lines
Round 3: Benchmark against 3 best published models. Where SinkAlert wins (multi-modal fusion) and falls short (no early warning, no temporal validation). 3 weakest links identified.
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ginnie_r4_roadmap.md
14 KB ยท 328 lines
Round 4: Top 10 actionable improvements ranked by impact. 3 novel ideas no other team will have. AWS services to add. Per-dimension pitch improvements with score estimates.
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Training YOLO Baseline Results
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yolo_baseline_results.md
501 B ยท 14 lines
CPU training baseline: mAP@50 = 0.25 (failed). Needs SageMaker GPU on full 7,598-image dataset.
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