Scaffold Reverso MVP pipeline structure

Set up the project skeleton per PLAN.md §4:
- src/ package: identifiers, disease, drugs, scoring, provenance
  with pydantic schemas and confidence-tier logic (working);
  data-pull/compute functions stubbed per their build week
- 5 starter notebooks (01-05) with PLAN-referenced steps
- tests/test_scoring.py: tier-assignment tests pass; scoring
  reference test xfail until Week 3
- docs/: recovery_test_report, data_sources, known_limitations skeletons
- pyproject.toml (requires-python >=3.11,<3.14), .gitignore, README
- data/ tree preserved via .gitkeep; raw/processed/results gitignored

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

notebooks/05_recovery_test.ipynb

@@ -0,0 +1,48 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 05 \u2014 Recovery test\n",
+    "\n",
+    "Week 4 (PLAN.md \u00a76). **Commit the pre-registered success criteria to git BEFORE running this notebook** (PLAN.md \u00a78, \u00a710).\n\nPull hydroxyurea + L-glutamine ranks and 5 negative-control ranks, compute pass/fail, examine the top 10, and fill in `docs/recovery_test_report.md`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.insert(0, '..')  # import the src package from notebooks/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from src import RESULTS_DIR\n",
+    "\n",
+    "ranking = pd.read_csv(RESULTS_DIR / 'ranked_candidates_v1.csv')\n",
+    "# Pull ground-truth + negative-control ranks; evaluate pre-registered criteria."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}