The spotlight notebook nb_sea_ad_001 (SEA-AD Cell-Type Vulnerability Analysis, is_spotlight=1) was seeded into the notebooks table on 2026-04-04T09:02:45 with rendered_html_path=/notebooks/nb_sea_ad_001 — a placeholder path pointing at no file. Three related rows also referenced non-existent artifacts:
notebooks.nb-analysis_sea_ad_001.rendered_html_path=site/notebooks/analysis_sea_ad_001.html — no such fileanalyses.analysis_sea_ad_001.artifact_path=site/notebooks/sea_ad_cell_vulnerability_analysis.ipynb — no such filehttps://scidex.ai/notebook/nb_sea_ad_001 rendered the "Notebook Not Rendered Yet" warning card. An earlier automation (task a06eb224, 2026-04-04) incorrectly marked this as a "false positive" because the HTTP endpoint returned 200 — but 200 with a warning card is not the same as a rendered notebook.The upstream task (70239694 D16.2: SEA-AD Single-Cell Analysis) was marked done without producing the notebook; the orchestrator max_tool_rounds fix (70239694_SOLUTION.md) was applied but the notebook generation step was never completed.
Deliver a credible, executable Jupyter notebook at nb_sea_ad_001 that:
@log_tool_call for provenance.analysis_sea_ad_001 to external literature evidence./notebook/{id} route can serve.site/notebooks/nb_sea_ad_001.ipynb exists, executes cleanly, and contains embedded output cellssite/notebooks/nb_sea_ad_001.html exists and contains jp-Notebook markup (compatible with _darkify_notebook)tool_calls table shows provenance rows for each tool invoked during generationnotebooks.nb_sea_ad_001, notebooks.nb-analysis_sea_ad_001, analyses.analysis_sea_ad_001python3 scripts/generate_nb_sea_ad_001.py [--force]data/forge_cache/seaad/*.json (idempotent re-runs)forge/seaad_analysis.py — reusable data collector wrapping 7 tool families over 11 AD-vulnerability genes + per-hypothesis literature queries. All calls route through instrumented tools.py functions.scripts/generate_nb_sea_ad_001.py — notebook generator: collects data, assembles cells, executes in-place via nbconvert.ExecutePreprocessor, renders HTML, updates DB rows.site/notebooks/nb_sea_ad_001.ipynb — 31 cells (16 markdown, 15 code), all executed, 2 embedded matplotlib figures.site/notebooks/nb_sea_ad_001.html — 552 KB nbconvert HTML export with jp-Notebook markup.data/forge_cache/seaad/*.json — 78 cached JSON bundles (gene annotations, Allen, STRING, Reactome, Enrichr, PubMed per hypothesis).tool_calls table, captured 2026-04-05)Immunoregulatory interactions between a Lymphoid and a non-Lymphoid cell (R-HSA-198933) is the top TREM2 pathway.This notebook uses aggregated / curated data sources, not per-cell SEA-AD snRNA-seq matrices. The following remain open:
Theallen_cell_types tool call returns Allen Cell Types API specimen metadata (electrophysiology/morphology), not SEA-AD snRNA-seq aggregates. This is a known limitation of the existing tools.py:allen_cell_types implementation.scripts/generate_nb_sea_ad_001.py is a template. To produce another spotlight notebook with this pattern, copy the script, change NOTEBOOK_ID, ANALYSIS_ID, TARGET_GENES, and the topical keywords in forge/seaad_analysis.py:_TOPIC_KEYWORDS. The cache directory naming mirrors the notebook id.
exchange_debate_seed_v2.json, falsification_power_plan_v1.json, gtex_brain_expression_v1.json) are already present on current origin/main; no duplicate restoration needed.data/analysis_outputs/analysis-SEAAD-20260402/donor_model_preregistration_v1.json, a preregistration-ready donor-level modeling plan that converts the five cell-type driver priors into concrete formulas, harmonized covariates, replication dataset requirements, confidence interval rules, negative controls, and Exchange resolution gates.benchmark_provenance_matrix_v1.json artifact while rebuilding the branch against current origin/main so unrelated stale-base drift is not carried forward.scripts/artifact_sweeper.sh rejection target no longer exists on current origin/main; data/scidex-papers has no unpushed local commits in this worktree, only a dirty checkout state outside this task's intended diff.origin/main already contains the iteration 4 retry artifacts (exchange_debate_seed_v2.json, falsification_power_plan_v1.json, gtex_brain_expression_v1.json), so this slice adds a new benchmark-provenance layer instead of re-pushing duplicate work.data/analysis_outputs/analysis-SEAAD-20260402/benchmark_provenance_matrix_v1.json, an auditable five-source x five-cell-type evidence matrix with directness weights, weighted vulnerability scores, leave-one-source-out sensitivity ranges, Exchange-use notes, and falsification hooks.origin/main to remove unrelated critical-file and persona/script/doc drift that caused review-gate failures.SEA-AD-gene-expression-analysis notebook sections: exchange_debate_seed_v2.json, falsification_power_plan_v1.json, and gtex_brain_expression_v1.json.find_repo_root() helper instead of hard-coding the task worktree path.seaad_marker_module_realdata_v1.json, seaad_marker_specificity_v1.csv, and scripts/build_seaad_marker_module_artifact.py from prior uncommitted slot work.ab6d4823-7145-4970-a2ae-f4ac6d71df37: planned a real SEA-AD summary-matrix increment for the live SEA-AD-gene-expression-analysis notebook.data/allen/seaad/medians.csv, trimmed_means.csv, and cell_metadata.csv; write a structured artifact; append an executed notebook section that contrasts real SEA-AD marker specificity with the existing benchmark/driver intervals.scripts/build_seaad_marker_module_artifact.py plus seaad_marker_module_realdata_v1.json and seaad_marker_specificity_v1.csv; the artifact summarizes 91,450 QC nuclei across 52 SEA-AD cluster columns for excitatory neurons, astrocytes, microglia/PVM, oligodendrocytes, and OPCs..claude/worktrees/slot-15-1775204013/site/notebooks/SEA-AD-gene-expression-analysis.ipynb / .html; the exported DE CSV now contains the full five-cell-type table instead of only the older microglia-vs-neuron slice.ab6d4823-7145-4970-a2ae-f4ac6d71df37: deepened the live SEA-AD-gene-expression-analysis spotlight notebook, not just the earlier nb_sea_ad_001 artifact.data/analysis_outputs/analysis-SEAAD-20260402/cell_type_driver_intervals_v2.json, a structured driver-prior artifact with interval estimates, testable predictions, and negative controls for excitatory-neuron, astrocyte, microglial, oligodendrocyte, and OPC hypotheses..claude/worktrees/slot-15-1775204013/site/notebooks/SEA-AD-gene-expression-analysis.ipynb: fixed stale main-checkout output paths, loaded the cross-dataset benchmark artifact, displayed five-cell-type vulnerability scores, plotted benchmark intervals, ranked candidate drivers, and embedded Exchange-ready debate/falsification sections..claude/worktrees/slot-15-1775204013/site/notebooks/SEA-AD-gene-expression-analysis.html via jupyter nbconvert --to html.ab6d4823-7145-4970-a2ae-f4ac6d71df37: added a candidate-driver test matrix so the notebook moves from ranked cell-type vulnerability into preregistration-ready hypothesis tests.data/analysis_outputs/analysis-SEAAD-20260402/driver_candidate_tests_v2.json, covering the five driver hypotheses with marker modules, shared covariates, primary endpoints, negative controls, assay-readiness priors, decisive replication thresholds, and falsifying patterns.site/notebooks/nb_sea_ad_001.ipynb, computing driver-test priority scores with leave-one-source-out sensitivity intervals and rendering a forest-style interval plot for Exchange triage.site/notebooks/nb_sea_ad_001.html via jupyter nbconvert --execute --to html.ab6d4823-7145-4970-a2ae-f4ac6d71df37: deepened the spotlight notebook beyond the prior microglia/neuron emphasis.data/analysis_outputs/analysis-SEAAD-20260402/cell_type_benchmarks_v1.json, a structured cross-dataset benchmark covering excitatory neurons, astrocytes, microglia, oligodendrocytes, and OPCs across SEA-AD 2024, Mathys 2019, Grubman 2019, Leng 2021, and Mathys multiregion 2024.site/notebooks/nb_sea_ad_001.ipynb: per-cell-type vulnerability scores with leave-one-benchmark-out intervals, 5 candidate cell-type-specific drivers with interval estimates, an Exchange-ready market/debate seed, and concrete falsification experiments.site/notebooks/nb_sea_ad_001.html via jupyter nbconvert --to html.notebooks.nb_sea_ad_001.rendered_html_path was a placeholder string, not a valid path. No ipynb had ever been generated.forge/seaad_analysis.py collector; ran full_collection() in 62 s (first invocation, uncached).scripts/generate_nb_sea_ad_001.py; produced ipynb (31 cells) and executed cleanly via ExecutePreprocessor.fix/nb-sea-ad-001-real-data.