4657fe715e3270ad568e196dd76660373ece14e0
The audit inferred (from code) that GF/DecayGF/KNN pop the OLDEST wave on resolution, while under bmPath bullets leave the arena in NON-FIFO order - so an outcome could be attached to the wrong wave. It also noted that `starved=0` does NOT rule this out. Both halves are now MEASURED. MISPAIRING RATE (10 DrussGT fixtures, real VirtualTracker, 344k resolutions/gun): gun bmPath mispair label err bmPoint mispair label err GuessFactor 36.48% 19.39% 18.24% 7.62% DecayGF 36.85% 19.52% 20.57% 8.64% KNN 57.91% 27.63% 29.75% 11.58% (starved = 0 everywhere, exactly as the audit predicted) So ~1 in 5 GF/DecayGF learning samples and ~1 in 4 KNN samples carried a WRONG guess-factor bin. This is a material corruption of the learning signal. FIX: the same fireTick-keyed ring scheme `tsetlin.nim`/`tm_selector.nim` already use - `slot = (fireTick*4 + bin) mod 1024` (period 256 ticks, longer than the ~91-tick max flight), looked up by exact key. Public interfaces unchanged; added `waveResolved`/`waveMispaired` integrity counters. AFTER: mispaired = 0 and starved = 0, both metrics, all three guns. EFFECT ON HIT RATE: SMALL AND NOT SIGNIFICANT. bmPath 4000 samples/gun: GuessFactor 23.20% -> 23.02% (-0.18pp, per-run sign-flip p=0.750) DecayGF 23.80% -> 24.25% (+0.45pp, p=0.625) KNN 18.27% -> 18.80% (+0.53pp, p=0.547) bmPoint: +0.05 / +0.33 / -0.15pp, p = 1.00 / 0.50 / 0.50. Per-run ranges overlap almost completely. A bullet-level z-test is anti-conservative (bullets within a fixture share a trajectory) and its KNN p=1.9e-16 cannot be trusted given ~10 effective independent runs. PLAIN READING: this is a CORRECTNESS fix, not a measurable hit-rate win. It removes a 36-58% mislabelling of the learning signal; the point estimates move by at most ~0.5pp, within run-to-run noise. Stated plainly rather than oversold. A REGRESSION IT CAUGHT IN ITSELF (and this explains the SIGSEGV another job saw and correctly attributed to a concurrent knn_gun.nim rewrite): the first implementation put an inline `array[1024, KNNWave]` (~100KB) inside each gun, which overflowed the default 8MB stack and made `test_power_selection` SIGSEGV. Causation was proven by stashing only the three gun files (test passed), then fixed by making the rings heap-backed `seq`. Verified: `test_power_selection` 3 PASS on the default stack, and zero inline `array[1024]` remain. Guards: test_wave_pairing 17 (new, pure), test_gun_harness 39, test_vbullet_metric 11, test_power_selection 3, test_adaptive_radar 41, test_tfil_ring_weights 24, test_power_policy 26, test_ram_decision 28. ModularBot compiles. Adds audit_wave_pairing.nim and compare_pairing.nim.
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