bench: measure RRF against the weighted sum — weighted wins, RRF not adopted

Reciprocal rank fusion was implemented but reachable only as a free function
over a linear scan, so its merits had never been tested. With both running
over the same HNSW + BM25 candidates on the full LongMemEval haystack (500
questions, real MiniLM embeddings):

  weighted 0.4/0.6   turn Hit@1 51.6%  Hit@5 81.4%  MRR 0.6430
  RRF k=60           turn Hit@1 45.0%  Hit@5 78.8%  MRR 0.5967

RRF lands almost exactly where the old 0.7/0.3 weighting did, and for the same
reason: it combines the stages by rank with equal influence, but on this corpus
BM25 alone beats the vector stage by 17.8pp at Hit@1, so treating them as peers
costs rank-1 accuracy. RRF's advantage is robustness when the stages' scores
are not comparable and there is nothing to tune against; here there is, so the
weighted sum stays the default. Recorded in BENCHMARKS.md with the reasoning,
including that this is a property of the corpus rather than a defect in RRF.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>

BENCHMARKS.md

@@ -597,6 +597,34 @@ Session-level:
 | Vector only | 85.4% | 94.2% | 96.6% | 0.8901 |
 | Hybrid | **88.2%** | **95.8%** | **97.8%** | **0.9158** |
 
+### Fusion method — weighted vs. RRF, full haystack, n=500
+
+Reciprocal rank fusion has been in the codebase since early on but was only
+reachable as a free function over a linear scan, so it had never been compared
+with the weighted sum on equal terms. `HDF5Memory::hybrid_search_with` now
+takes a `Fusion`, and both run over the same HNSW + BM25 candidates:
+
+| Mode | turn Hit@1 | Hit@5 | Hit@10 | MRR | session Hit@1 | session MRR |
+|---|---|---|---|---|---|---|
+| BM25 only | **53.8%** | 75.0% | 81.6% | 0.6320 | 86.2% | 0.8948 |
+| Vector only | 36.0% | 71.8% | 81.6% | 0.5031 | 85.4% | 0.8901 |
+| **Weighted 0.4 / 0.6** | 51.6% | **81.4%** | **87.8%** | **0.6430** | **91.0%** | **0.9347** |
+| RRF (k=60) | 45.0% | 78.8% | 87.6% | 0.5967 | 89.6% | 0.9253 |
+
+**RRF loses to the tuned weighted sum** — 6.6pp of turn Hit@1 and 0.046 of MRR
+— and lands almost exactly where the old `0.7/0.3` weighting did (44.2% / 
+0.5856). That is not a coincidence: RRF combines the two stages by rank with
+*equal* influence, and on this corpus the stages are not equally good. BM25
+alone beats the vector stage by 17.8pp at Hit@1, so any scheme that treats them
+as peers gives up rank-1 accuracy, and RRF discards the score magnitudes that
+would say which stage to believe.
+
+This is a property of the corpus, not a defect in RRF: its selling point is
+robustness when the two stages' scores are not comparable and there is no
+labelled data to tune against. Here there is, so the weighted sum is kept as
+the default. `Fusion::Rrf` remains available for callers whose stages are more
+evenly matched.
+
 ### Weight sweep — full haystack, n=500
 
 `0.7/0.3` was a documented default, never a searched one. Sweeping
@@ -639,7 +667,8 @@ BM25 at Hit@1. Both dominate `0.7/0.3`.
 
 The rows below are kept at the three original settings because they are what the
 mode ablation measured — read them as "the shape of each stage in isolation",
-and take the operating point from the sweep.
+and take the operating point from the sweep. `0.4/0.6` is now the shipped
+default (`hybrid::DEFAULT_FUSION`).
 
 The same pattern shows up independently in omni-cortex's four-signal RRF ablation,
 where adding BM25 to a dense retriever raised nDCG@5 while lowering Hit@1 and MRR.