SirStone
9cd6e9b8ce
shipped metric The radial TM beats Linear on bmPoint, but its head never beat the majority baseline after the label bias was fixed - suggesting the win is a constant lean rather than learning. So: sweep a stateless constant short-range offset (new `common_libs/guns/radial_offset.nim`, no learning at all) against the learned TM. VERDICT (measured, offline range, seeds=3, 18 paired runs, 231 TM rounds): 1. **bmPoint - REPLACE the TM with a constant.** `RO_s0.95` (aim distance x0.95) TIES it early (9/9, p=1.0) and BEATS it overall (15/3, p=0.0075; 7.47% vs 6.89% per-run mean). A fixed -20px does the same. The head never beats its majority baseline (56.2% vs 57.2%). 2. **bmPath (the SHIPPED metric) - the radial avenue is a DEAD END.** TMRadial is a systematic LOSS there (2/16, p=0.0013); every constant is within +-0.2pp; the only real bmPath effect is the BotRadius clamp. So the radial shift cannot help the shipped configuration. 3. The per-adversary optimum DOES vary (fixed -10 for crazy, -30 for tr_crazy, scale 0.95 for three others) - but ONE GLOBAL CONSTANT still beats the adaptively-trained head, so the "fragility justifies learning" argument FAILS. THE REAL FINDING UNDERNEATH, and it generalises beyond this gun: the base linear prediction systematically OVERSHOOTS. Measured raw per-tick base radial error has mean -71 to -100 px; the enemy is NEARER than the prediction in 63-81% of shots and farther in only 4-14%, CONSISTENT ACROSS ALL SIX CAPTURES. Radial label histogram [415166,126461,120325,44694,19351] = 57.2% majority class, mean label -82.3 px, mean applied shift -37.6 px. So the net-short bias is a GENUINE property of these range-holders against a constant-velocity extrapolation (they decelerate and turn, so the true position is closer than the straight-line guess) - NOT a fixture artefact. That is worth chasing for the guns that actually ship. Caveat: bmPoint is not the shipped metric (bmPath won the real-hit-rate A/B for SELECTION), so a bmPoint win is not yet evidence of a real win. That needs a live test - and the natural target is Pattern, which is now the default and best gun. Adds radial_offset.nim + sweep_radial_offset.nim; tm_pattern.nim gains additive instrumentation only (radial label mean and applied-shift mean; no behaviour change, and test_tm_pattern_registration still passes all 20 checks).