Join the product's source ids to the benchmark's before scoring

The merged database names a source by content hash (`11089_4f2a...`) while the
frozen sets name the same file by its corpus id, so every arm scored 0.000 until
load_atoms joined atoms through sources.path. It now returns corpus ids and
refuses an atom it cannot trace to a corpus file.

Also fixes found by running the harness:
- merge rebuilt atom_fts from the deduped atoms table; two attempts on one file
  left 288,266 fts rows for 165,973 atoms.
- merge accepts the two honest reasons a corpus file has no product source
  (500 byte-identical LongMemEval sessions collapse under content hashing, and
  12 photos that ONNX Runtime cannot decode) and reports them.
- --arms used action=extend against a non-empty default, so naming two arms ran
  seven.
- the dense cache is keyed by the atom set, so a scale-curve subset cannot be
  scored with full-corpus vectors.
- write_markdown crashed on a run that covered only some modalities.

bench/reports/baseline.json

@@ -0,0 +1,77 @@
+{
+ "arms": [
+  {
+   "arm": "bm25_only",
+   "by_modality": {
+    "pdf": {
+     "abstention_rate_answerable": 0.0,
+     "abstention_rate_unanswerable": 0.0,
+     "hit_at_10": 1.0,
+     "hit_at_10_wilson_lower": 0.6755924351161198,
+     "mrr": 0.725,
+     "n_answerable": 8,
+     "n_unanswerable": 2,
+     "ndcg_at_10": 0.7883559233904859,
+     "recall_at_1": 0.625,
+     "recall_at_10": 1.0,
+     "recall_at_5": 0.875,
+     "wrong_holder_confidence_unanswerable": 1.0
+    }
+   },
+   "latency_seconds": {
+    "max": 1.3251221780083142,
+    "mean": 0.8729710359009915,
+    "p50": 0.8812561564991483,
+    "p95": 1.2068847050097244,
+    "queries": 10
+   },
+   "overall": {
+    "abstention_rate_answerable": 0.0,
+    "abstention_rate_unanswerable": 0.0,
+    "hit_at_10": 1.0,
+    "hit_at_10_wilson_lower": 0.6755924351161198,
+    "mrr": 0.725,
+    "n_answerable": 8,
+    "n_unanswerable": 2,
+    "ndcg_at_10": 0.7883559233904859,
+    "recall_at_1": 0.625,
+    "recall_at_10": 1.0,
+    "recall_at_5": 0.875,
+    "wrong_holder_confidence_unanswerable": 1.0
+   }
+  }
+ ],
+ "chance": {
+  "corpus_sources": 50278,
+  "recall_at_1": 1.9889414853415013e-05,
+  "recall_at_10": 0.00019889414853415012,
+  "recall_at_5": 9.944707426707506e-05
+ },
+ "meta": {
+  "answerable": 8,
+  "corpus_manifest_sha256": "8fc1ed861c891d778853d41107630869f9eb267a669c5d1038e389de80114347",
+  "corpus_sources": 50278,
+  "generated_at": "2026-10-06T20:42:42+00:00",
+  "git_commit": "fc0698c2426c373e32c361a816523351a1e3fcb7",
+  "limit_per_modality": 10,
+  "machine": {
+   "cpus": 32,
+   "release": "6.18.40.1-microsoft-standard-WSL2",
+   "system": "Linux"
+  },
+  "models": {
+   "dense": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
+   "rerank": "BAAI/bge-reranker-base"
+  },
+  "python": "3.14.4",
+  "queries": 10,
+  "sets": {
+   "code": "ea7e248386350f95132a398f3710f6ce5f09424ca614fd88c618207f667a553e",
+   "conversation": "dc106d90e7749bee8be01b1fab3b645a5459d7527ef40e7fbf983677d5898d11",
+   "image": "1c74488375c7ec9f3182964d51a5e506273bfd5cf3d126725c3cc431a8333128",
+   "pdf": "0cec488e660bf1bfa7ccfc72dbae8b7e3005f0b6a0255028e502296d4ecd4536",
+   "ui_screenshot": "2269dd623e67cd851fb3f6b24a4556a8462a37db98e12ad79577c5830167c7c5",
+   "video": "4973231d9f16d214b14923d79a34b85c3d2b423624dea752b1ee91ba09ff778c"
+  }
+ }
+}