SirRoboGarage/docs/gun_campaign.md

Gun campaign — ledger

Goal (owner's mandate, 2026-09-26 overnight): the movement campaign produced a replicated champion (TR_MOVEMENT=strafe, docs/movement_campaign.md) which a parallel job is shipping. "Continue until you found an amazing movement. When found do the same over for a gun." This file is the GUN campaign's single source of truth: later jobs append a ## Batch N section and never edit an earlier one (a wrong earlier number gets a correction line, not a rewrite). This file is the gun successor to docs/movement_campaign.md; read that first, then this.

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OUTCOME (read this first)

The shipped gun is UNCHANGED: onlyPattern — the rack admits Pattern only (common_libs/gun_harness/selector.nim, commit e0666a5). Nothing beat it. The gun design space explored here is CLOSED on evidence, not on belief.

Headline (MEASURED). Four frozen-binary tournament sessions on the frozen 15- and 33-opponent panels: 1,233 battles (phase 1: 270 + 297; phase 2: 270 + 396), 0 failed, 0 never-started, 0 liveness exclusions. Each session is ONE binary built from git archive HEAD; arms differ only by env; movement is pinned TR_MOVEMENT=strafe in every arm, so every delta is a pure gun delta. With the earlier 16-gun selector campaign (≈660 battles) the gun ledger now stands on ≈1,900 measured battles. What was detectably worse: knn (−39.3 dmg/run, 0/15 opponents; −0.62 wins/run, p=0.012) and, on the wider 33-opponent panel, TMHorizon (−10.4 dmg/run, sign p=0.035). What was not distinguishable (inside the MDE, no verdict): bitbrain, tmhorizon@15, rack_pk, rack_pt, len6, len16, depth100, the two radial controls.

CLOSED axes (one-line reason each)

axis	reason it is closed
other single guns	knn detectably worse; bitbrain a wash measured 3× (−3.6 / +10.3 / +1.8 dmg/run, all inside their MDEs); TMHorizon worse on 33 (docs/gauntlet_bitbrain_vs_pattern.md, Batches 1–2)
2-gun selector racks	rack_pk nominally below pattern on wins; rack_pt == tmhorizon-alone → the selector just picks the corrector (## Batch 1)
selector mechanics	the virtual-fitness selector is negative value at every rack size tested (16, lean8, lean6, pairs); it never manufactured a win (docs/selector_negative_value.md)
gun allocation (share)	**forced TR_RACK_SHARE schedules (50/50, 70/30; PB/PT/PK) never beat pattern by the pre-registered rule; the only detectable effect is negative (50/50 KNN, −11 dmg/run, p=0.042); the observed ~66/34 split was already right (## Allocation)
lead amplitude	a full gain sweep (1.0/1.5/2.0/3.0) makes Pattern strictly worse at every range band — the lever is lead information, not amplitude (docs/bitbrain_campaign.md §0.3.2)
Pattern's own match-length / history params	len6's single-session +0.49 wins (p=0.039 on 15) reversed to a wash on 33 (−0.04, p=1); len16/depth100 flat; two batches, no replication (## Phase 2)
radial knobs (TR_PATTERN_RAD_*)	bearing-invariant by construction (job j99 proved bmPath is a structural no-op and scale/offset cannot change the aim bearing); in Batch 2 rad_offset is nominally negative

THE ONE OPEN AXIS

A genuinely new source of lead INFORMATION — not another knob on BitBrain/TMHorizon (both measured neutral→negative), not amplitude (dead), not radial (bearing-invariant). The standing mechanism is docs/bitbrain_campaign.md §0.3.3: at 450+ px Pattern's own lead correlation with the required lead is only 0.165, so it is adding variance to a nearly uninformative signal.

Honest caveat (MEASURED, docs/state_window_gate.md). The best surviving idea from the state line — a single wave-relative state at Q=4 — does carry signal at coarse resolution: it predicts the miss-offset bin on held-out battles at 0.4094 (vs 0.2348 majority), but those bins are 36/42/60 px wide = 4.58/5.34/7.63° at 450 px, and its implied hit probability is still the base rate (~0.09) — i.e. it is informative about which side the miss falls on, not about whether the shot hits. The live hit window is atan(18/450) = 2.29° half-width; the measured signal is at ~4.6–7.6°, not at the ~2° the 450 px hit window needs. A temporal window does not fix this (the window gate is negative; long contexts never recur). So the open axis is a new information source that resolves the arrival offset to better than ~2°, which does not exist yet.

Cost estimate for trying it (INFERRED). Build and offline-gate the new information source first — require it to beat Pattern's 0.165 lead correlation and, ideally, predict the arrival offset to <2.29° on held-out shots (days of work; the offline instruments exist, e.g. common_libs/tests/state_window_gate.py). Only then spend a live batch: one frozen binary, 6 env-only arms × 15 opponents × 3 runs × 3 rounds = 270 battles ≈ 1–2 h wall at conc 6 with --wait-arena (exact command in How to run a batch). Do not open with a live batch.

What would change our mind

A named new information source that (1) offline predicts the arrival offset to better than the ~2.29° hit half-window at 450 px on held-out battles and (2) in a live frozen-panel batch beats pattern on wins/run with the winning metric's CI excluding 0 and sign-flip p<0.05 while damage is not detectably down. A damage-only gain without wins is the ring-mover trap and does not count.

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What changed tonight (2026-09-26)

• SHIPPED: nothing in the gun. The rack is still onlyPattern.
• NOT shipped, and why: every candidate (other gun, small rack, selector mechanic, match-length/history parameter, radial knob) failed to beat pattern beyond the MDE on the frozen panels. Phase 2's one signal (len6, +0.49 wins/run on 15 opponents) did not replicate on 33 opponents. The only shipped change of the night is the movement default (tfil -> strafe, see docs/movement_campaign.md); the gun was left untouched.
• Revert: no gun revert is needed (no gun default changed). Movement: TR_MOVEMENT=tfil.
• Reproduce the key gun evidence (one command + the analyzer) — phase 2, Batch 2, the session that killed len6:

  TOURNAMENT_NIMCACHE=/tmp/nc_j123 \
  tools/ab/tournament_run.sh \
      --arms tools/ab/arms_gun_b4.txt \
      --panel tools/ab/panel_gun_b2.txt \
      --runs 3 --rounds 3 --conc 6 --wait-arena 45 \
      --reference pattern \
      --outdir /tmp/ab/j123_b2
  python3 tools/ab/tournament_analyze.py /tmp/ab/j123_b2 --reference pattern
  

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0. The question

The shipped rack admits Pattern only (onlyPattern). That decision was taken because the virtual-fitness selector measured negative value at every rack size tested, and Pattern is the best single gun by the DrussGT hit-rate table (docs/selector_negative_value.md, docs/gun_rack_analysis.md, commit e0666a5). But every one of those measurements — like every pre-campaign movement claim — is DrussGT-heavy, and the movement campaign's standing lesson is that a one-opponent result is not a result.

So Batch 1 asks the direct question, on a frozen 15-opponent panel:

Does any rack gun, or any small gun configuration, beat the shipped Pattern on damage/run AND round wins across 15 opponents — or is onlyPattern CONFIRMED rather than merely assumed?

A null is a successful outcome here: it upgrades onlyPattern from an assumption to a measured verdict across the panel, which is itself valuable.

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1. Protocol (identical to the movement campaign; the instrument is reused verbatim)

tools/ab/tournament_run.sh + tools/ab/tournament_analyze.py + tools/ab/panel_movement.txt (frozen panel), reused unchanged. The unit of evidence is the number of opponents, not the number of runs.

Element	Rule
Subject	ONE frozen binary built from git archive HEAD (tournament_run.sh records commit + binary sha256 in session.json)
Arms	env dicts only — no per-arm rebuild, ever; the arm file is a committed file (tools/ab/arms_gun_b1.txt)
Panel	the frozen tools/ab/panel_movement.txt (15 opponents). Adding/removing an opponent starts a new batch number
Pairing	per opponent: average the arm's runs, subtract the reference's average for that same opponent → one delta per opponent; then aggregate
Isolation	per-run bot dir + classic data dir, ephemeral ports, own process group; cleanup only by this session's outdir
Serialization	one battle fleet at a time via --wait-arena; never a broad pkill robocode_shim
Liveness	every declared env token must appear verbatim in OUR bot's own raw-env report, else the run is excluded and named
Never shipped	this is a measurement campaign: git status clean, shipped defaults untouched, .gitignore untouched

Movement-default flip note (MEASURED). During this job a parallel job (j120, commit 3fd6db9) flipped the shipped TR_MOVEMENT default from tfil to strafe. Batch 1 built before the flip, Batch 2 after. Every arm in both batches declares TR_MOVEMENT=strafe, so the effective movement is identical and the two batches are directly comparable — the pin did its job. The reference rack lines in the boot reports read PATTERN for pattern, and the active 1v1 rack reads BITBRAIN / TMHORIZON / KNN for the overridden arms.

Movement is PINNED in every arm: TR_MOVEMENT=strafe

Reason (hard rule). A movement-default flip is landing from job j120 during this run, so the default engine can change underneath us. Every arm therefore sets TR_MOVEMENT=strafe explicitly. This (a) removes movement as a confound, (b) makes all arms share exactly one movement, so every delta is a pure gun delta, and (c) satisfies the analyzer's liveness rule for every arm (each declared token must appear verbatim; an undeclared leaked TR_MOVEMENT is fatal, but here every arm declares it). The reference arm is therefore the shipped gun rack under the pinned movement, not under the (mutable) default.

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2. Pre-registered decision rules (fixed BEFORE Batch 1 ran)

1. Primary metrics: damage/run and ROUND WINS. Secondary/explanation only: damage taken/run, incoming hit rate, mean distance. Never hit rate alone — that trap has inverted six verdicts in this project.
2. BETTER than the reference iff one primary metric is up with a cross-opponent sign test p < 0.05 while the other does not go down; the mirror image for WORSE. Anything else is NOT DISTINGUISHABLE (a real answer, not a failure). Both the strict reading (the other metric's mean delta >= 0) and the substantive reading (not detectably down: not significant and smaller than that metric's MDE) are printed.
3. A verdict must survive the between-opponent spread: the pooled mean delta is reported with the SD across opponents, its SE, a 95% CI, and the MDE (α=0.05 two-sided, 80% power). An effect smaller than the MDE is reported as not detectable — never as absent, never as a win.
4. Somewhere to stop: if no arm beats the shipped pattern by rule 2 in Batch 1 and no arm shows a >= +MDE damage gain with p<0.10, then the gun stage's first phase is closed with "the shipped onlyPattern rack is the best gun configuration we have measured across the panel" — that is a successful outcome, and the campaign moves to a named next axis rather than inventing more arms. See What would make us stop.
5. No promotion off a single metric, a single opponent, or a single run. A change that wins damage by losing wins (or vice-versa) is not a win.
6. Every batch is shot with a pre-registered prediction stated in its section before the battles finish; a prediction that turns out wrong is recorded as wrong.

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3. Stage 0 — what we already know (given, not re-derived)

fact	value	source
shipped rack	onlyPattern (id 5), all other guns off	common_libs/gun_harness/selector.nim
why	selector measured negative value at every rack size (16, lean8, lean6, pairPC/PK/PL) and 10/10 adversaries	docs/selector_negative_value.md, docs/gun_rack_analysis.md
Pattern hit rate vs DrussGT	~10.8%	given
KNN / Linear / Circular / WallBounce / GF vs DrussGT	5.6 / 3.0 / 2.9 / 2.7 / 2.1 %	given
BitBrain when idle	== Pattern (30 runs/arm: 97/210 vs 97/210 wins)	docs/bitbrain_vs_tmhorizon_ab.md
BitBrain across 32 legacy opponents	neutral: -3.6 dmg/run, +0.02 wins/run, p=0.53/0.91	docs/gauntlet_bitbrain_vs_pattern.md
lead amplitude	dead axis — full gain sweep {0, 0.25-1.0, 1.0, 1.25, 1.5, 2.0} run, nothing beats Pattern	docs/bitbrain_campaign.md
offline prediction checks	veto-only — may kill a design, never select one	docs/offline_harness_trust.md
spinner-specific claim	UNTESTED: no constant-turn spinner exists in the legacy roster (a note for a later job, not built here unless nearly free)	docs/gauntlet_bitbrain_vs_pattern.md

Movement context (why the pin): the movement champion is TR_MOVEMENT=strafe at its current defaults (range 325, tol 25, tilt 15/0.10); it replicated its win over the shipped tfil in four independent sessions (Batch 4: 52.6% vs 38.5% round-win rate). Movement is held constant at that champion for every gun arm.

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Batch 1 — does anything beat the shipped Pattern?

Design. One frozen binary, six env-only arms, one frozen panel (tools/ab/panel_movement.txt, 15 opponents: 5 dodger, 3 pattern, 1 wall-follower, 1 corner-camper, 1 spinner, 1 rammer, 1 brawler, 2 aggressive megas), 3 runs × 3 rounds per (opponent, arm) = 270 battles. Arm file: tools/ab/arms_gun_b1.txt. Reference: pattern.

#	arm	env	what it isolates
1	pattern	TR_MOVEMENT=strafe	the arm to beat (shipped onlyPattern rack)
2	bitbrain	+ TR_RACK_PATTERN=off TR_RACK_BITBRAIN=both TR_BITBRAIN_GAINS=1.0,1.25,1.5,2.0 TR_BITBRAIN_MEM=decay	BitBrain-only, learned gain (panel replication of the 32-opp gauntlet at the pinned-movement standard)
3	tmhorizon	+ TR_RACK_PATTERN=off TR_RACK_TMHORIZON=both	TMHorizon-only corrector (predicted to lose; never panel-tested)
4	knn	+ TR_RACK_PATTERN=off TR_RACK_KNN=both	best non-Pattern single gun (never panel-tested)
5	rack_pk	+ TR_RACK_KNN=both	Pattern + KNN, selector ON (different-family hedge)
6	rack_pt	+ TR_RACK_TMHORIZON=both	Pattern + TMHorizon, selector ON (corrector-family hedge)

(+ = the pinned TR_MOVEMENT=strafe is present in every arm; see §1.)

Pre-registered prediction (written BEFORE the battles finished):

1. No arm beats pattern on BOTH primaries, and the point estimates sit inside the MDE. onlyPattern is confirmed across the panel.
2. bitbrain is a wash vs pattern (replicating the 32-opponent gauntlet: ±3.6 dmg/run, ≈0 wins) — the DrussGT-only gain-config penalty does not carry.
3. tmhorizon is WORSE than pattern (its own offline work predicts it needs ~80% side accuracy and can reach ~60%); no damage win, no win win.
4. knn is WORSE than pattern on damage (its DrussGT hit rate is roughly half Pattern's) and not better on wins.
5. The two small racks do not beat pattern; rack_pk lands closer to Pattern than knn-alone does (the selector at least partially hedges back), but the selector's poor ranking keeps it below the reference.
6. If any surprise exists, it is a rack arm on damage without wins — the ring-mover mirror-image trap — and it will not be read as a win.

Outcome — direct answer

MEASURED. Session /tmp/ab/j121_g1, commit 1d8143a15e4a038c39dfc2153ff518fa003b8612 (the pre-registration commit), frozen binary sha256 aa49a45fec20…, 15 opponents × 6 arms × 3 runs × 3 rounds = 270 battles, 0 failed, 0 never started, 0 liveness exclusions. Every arm declared TR_MOVEMENT=strafe, verified in each bot's own raw-env report; the reference rack line reads PATTERN for pattern and the overridden rack reads BITBRAIN / TMHORIZON / KNN for the others.

DIRECT ANSWER (MEASURED, n=15 opponents): NO — nothing beats the shipped Pattern across the panel on damage/run AND round wins. Every arm except knn is NOT DISTINGUISHABLE from pattern under both the strict and the substantive reading of the pre-registered rule. The best nominal challenger, tmhorizon, is +0.13 wins/run (MDE 0.36) and +8.7 dmg/run (MDE 13.8) — an effect ~3× smaller than the design can detect — and bitbrain is +0.11 wins / +10.3 dmg, also inside the MDE. knn is detectably WORSE on both primaries. The shipped onlyPattern rack is therefore CONFIRMED rather than merely assumed, at the resolution of this panel. That is a real result, not a failure.

Pooled dashboard (all valid runs — explanation only, NOT the verdict)

arm	runs	dmg/run	dmg taken/run	wins/run	round wins	win rate	incoming hit rate	mean distance
pattern (REF)	45	99.6	155.9	1.51	68/135	50.4%	12.84%	435
bitbrain	45	109.9	151.2	1.62	73/135	54.1%	12.87%	427
tmhorizon	45	108.3	153.7	1.64	74/135	54.8%	12.53%	428
knn	45	60.3	175.7	0.89	40/135	29.6%	13.31%	430
rack_pk	45	107.3	161.3	1.42	64/135	47.4%	13.65%	432
rack_pt	45	105.3	149.9	1.64	74/135	54.8%	12.90%	424

Cross-opponent aggregation (the verdict layer, damage + wins)

arm	metric	mean Δ	spread (SD)	95% CI	sign test (wins/n)	p(sign)	p(sign-flip)	Wilcoxon p	MDE
bitbrain	damage	+10.34	16.65	[+1.12, +19.57]	11/15	0.1185	0.03247	0.05006	12.05
bitbrain	wins	+0.11	0.48	[-0.16, +0.38]	6/9	0.5078	0.4922	0.4764	0.35
tmhorizon	damage	+8.71	19.10	[-1.86, +19.29]	11/15	0.1185	0.09918	0.1183	13.82
tmhorizon	wins	+0.13	0.50	[-0.14, +0.41]	5/9	1.0	0.4062	0.3118	0.36
knn	damage	−39.33	23.15	[−52.15, −26.51]	0/15	6.1e-5	6.1e-5	0.0007	16.75
knn	wins	−0.62	0.59	[−0.95, −0.30]	1/11	0.01172	0.001953	0.004948	0.43
rack_pk	damage	+7.68	32.09	[−10.10, +25.45]	9/15	0.6072	0.423	0.5895	23.21
rack_pk	wins	−0.09	0.60	[−0.42, +0.24]	6/11	1.0	0.6738	0.5932	0.43
rack_pt	damage	+5.69	16.50	[−3.45, +14.83]	10/15	0.3018	0.2026	0.2681	11.93
rack_pt	wins	+0.13	0.41	[−0.10, +0.36]	6/10	0.7539	0.3242	0.1997	0.30

The pre-registered verdict (verbatim)

rank	arm	Δwins/run	Δdmg/run	sign test wins	sign test dmg	verdict (strict)	verdict (substantive)
1	tmhorizon	+0.13	+8.7	5/9 p=1	11/15 p=0.1185	not distinguishable	not distinguishable
2	rack_pt	+0.13	+5.7	6/10 p=0.7539	10/15 p=0.3018	not distinguishable	not distinguishable
3	bitbrain	+0.11	+10.3	6/9 p=0.5078	11/15 p=0.1185	not distinguishable	not distinguishable
4	rack_pk	−0.09	+7.7	6/11 p=1	9/15 p=0.6072	not distinguishable	not distinguishable
5	knn	−0.62	−39.3	1/11 p=0.01172	0/15 p=6.104e-05	WORSE	not distinguishable

Reference pattern: 99.6 dmg/run, 1.51 wins/run, 12.84% incoming, 435 px.

Reading (MEASURED, with the mechanism)

• knn is a clean, large loss and is dropped. It deals −39 dmg/run and loses −0.62 wins/run, positive on 0/15 opponents on damage and 1/11 on wins (p=6e-5 / p=0.012). Its incoming hit rate is no worse (13.31% vs 12.84%) — it simply cannot aim: the same movement, a worse gun.
• The two small racks do not beat pattern. rack_pk (Pattern+KNN, selector ON) is not the average of Pattern and KNN: it recovers most of KNN's damage loss (+7.7 vs KNN-alone's −39.3) but still lands nominally below Pattern on wins (−0.09). rack_pt (Pattern+TMHorizon) is statistically indistinguishable from tmhorizon-alone — adding Pattern to the rack changes nothing, i.e. the selector picks the corrector essentially always. The selector's 16-gun negative verdict reproduces at a 2-gun rack: it does not manufacture a win it did not have.
• The only signal is a damage-side hint on the two Pattern-lead correctors (bitbrain +10.3, tmhorizon +8.7, both 11/15 opponents). It is below the MDE (12.0 / 13.8) and not significant by the pre-registered sign test (p=0.1185), so it is not a win and not a null. Note the sign-flip test on the mean is nominally significant for bitbrain (p=0.032) while the sign test is not — the positive deltas are larger than the negatives — but with 5 arms compared this is not compelling after multiplicity, and the effect is under the MDE. This is exactly the "damage without wins" pattern this project keeps paying for (the ring mover: +31 dmg/run and fewer wins); here the win deltas (+0.11/+0.13) are themselves sub-MDE.
• The reference is stable: pattern under TR_MOVEMENT=strafe measures 99.6 dmg/run and 50.4% round wins here, matching the movement campaign's strafe reference in Batch 4 (103.5 dmg/run, 52.6%) — same movement, same panel, different job.

Pre-registered predictions — scorecard (an honest count)

#	prediction	outcome
1	no arm beats pattern on both primaries, point estimates inside the MDE; onlyPattern confirmed	CORRECT
2	bitbrain is a wash vs pattern (gauntlet: −3.6 dmg, ≈0 wins)	CORRECT on the verdict, WRONG on the point estimate: +10.3 dmg here vs −3.6 in the 32-opponent gauntlet; both inside their MDEs. Direction differs, verdict (wash) holds
3	tmhorizon is WORSE than pattern (its own docs predict it loses)	WRONG: it is nominally better on both primaries (+8.7 dmg, +0.13 wins), though not distinguishable
4	knn is WORSE than pattern on damage, not better on wins	CORRECT (detectably on both)
5	the small racks do not beat pattern; rack_pk lands closer to Pattern than knn-alone	CORRECT
6	any surprise is a rack arm on damage without wins	PARTLY CORRECT: the nominal damage edge is on the single-gun correctors and the racks; every one of them is win-flat

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Batch 2 — wider-panel calibration of the damage-side hint

The Batch-1 answer is decisive on the primary question (nothing beats pattern) but the two corrector arms carry a sub-MDE damage hint that rule 3 forbids calling either way. Resolving it needs more opponents, not more runs, so this batch re-runs exactly those two arms plus the reference on a wider panel.

Design. One frozen binary, three env-only arms, panel tools/ab/panel_gun_b2.txt = the j117 32-opponent legacy roster minus Aurora (inert in j117: one fire in 6 battles — it cannot reveal a gun regression) plus SpinBot = 33 opponents (a superset of Batch 1's 15). 3 runs × 3 rounds = 297 battles, --conc 6, --wait-arena. Arm file: tools/ab/arms_gun_b2.txt. Reference: pattern. Movement pinned TR_MOVEMENT=strafe in every arm (same rationale as Batch 1).

#	arm	env	role
1	pattern	TR_MOVEMENT=strafe	reference
2	bitbrain	+ TR_RACK_PATTERN=off TR_RACK_BITBRAIN=both TR_BITBRAIN_GAINS=1.0,1.25,1.5,2.0 TR_BITBRAIN_MEM=decay	largest Batch-1 damage edge (+10.3)
3	tmhorizon	+ TR_RACK_PATTERN=off TR_RACK_TMHORIZON=both	second Batch-1 damage edge (+8.7)

Pre-registered prediction (written BEFORE the battles finished):

1. The +10 dmg/run hint does not survive the wider panel: bitbrain and tmhorizon damage deltas fall toward zero and stay inside the new (smaller) MDE; the per-opponent sign test remains non-significant. Rationale: both arms come from the same Pattern-lead-correction base, and the prior 32-opponent gauntlet measured bitbrain at −3.6 dmg/run on a largely overlapping roster; +10 on 15 opponents is plausibly a small-panel fluctuation.
2. Round wins remain flat for both arms — if anything they regress toward zero.
3. If instead the damage hint survives at a significant cross-opponent sign test with wins not down, it is recorded as the first gun to beat pattern by rule 2 — and the campaign immediately looks for what the corrector is exploiting. That would be a genuine up-set, and it would not be spun as a null.

Outcome — Batch 2

MEASURED. Session /tmp/ab/j121_g2, commit c343c00aaf800bc05ce9bf1b277054c11f5f577c, frozen binary sha256 d267ab78f6ce…, 33 opponents × 3 arms × 3 runs × 3 rounds = 297 battles, 0 failed, 0 never started, 0 liveness exclusions.

A movement-default flip landed between the two batches (commit 3fd6db9, TR_MOVEMENT default tfil → strafe; the only source change). Because every arm in both batches pins TR_MOVEMENT=strafe, the effective movement is identical in Batch 1 and Batch 2 — the batches are directly comparable and the gun comparison is unconfounded. This is exactly what the pin was for.

DIRECT ANSWER (MEASURED, n=33 opponents): the Batch-1 damage hint did NOT survive. bitbrain collapses to +1.8 dmg/run (19/33 opponents, sign test p=0.49) with +0.11 wins/run — a wash. tmhorizon reverses sign and is detectably WORSE on damage: −10.4 dmg/run (10/33 opponents, sign test p=0.035, sign-flip p=0.0047, 95% CI [−17.2, −3.6]) at unchanged wins (−0.03). The only open signal in Batch 1 was a small-panel fluctuation, and the wider panel resolves it against the correctors. Combined with Batch 1: nothing beats the shipped Pattern on damage/run AND round wins; onlyPattern is CONFIRMED on 15 opponents and again on 33.

Pooled dashboard (all valid runs — explanation only, NOT the verdict)

arm	runs	dmg/run	dmg taken/run	wins/run	round wins	win rate	incoming hit rate	mean distance
pattern (REF)	99	131.2	126.4	1.90	188/297	63.3%	12.93%	417
bitbrain	99	133.0	126.7	2.01	199/297	67.0%	12.91%	417
tmhorizon	99	120.8	133.2	1.87	185/297	62.3%	13.04%	422

Cross-opponent aggregation (the verdict layer, damage + wins)

arm	metric	mean Δ	spread (SD)	95% CI	sign test (wins/n)	p(sign)	p(sign-flip)	Wilcoxon p	MDE
bitbrain	damage	+1.80	18.95	[−4.67, +8.26]	19/33	0.4869	0.5914	0.5675	9.24
bitbrain	wins	+0.11	0.48	[−0.05, +0.28]	12/19	0.3593	0.2436	0.5716	0.24
tmhorizon	damage	−10.40	20.01	[−17.22, −3.57]	10/33	0.03508	0.00472	0.006975	9.76
tmhorizon	wins	−0.03	0.59	[−0.23, +0.17]	9/19	1.0	0.8459	0.4804	0.29

The pre-registered verdict (verbatim)

rank	arm	Δwins/run	Δdmg/run	sign test wins	sign test dmg	verdict (strict)	verdict (substantive)
1	bitbrain	+0.11	+1.8	12/19 p=0.3593	19/33 p=0.4869	not distinguishable	not distinguishable
2	tmhorizon	−0.03	−10.4	9/19 p=1	10/33 p=0.03508	WORSE	WORSE

Reference pattern: 131.2 dmg/run, 1.90 wins/run, 12.93% incoming, 417 px.

Reading

• BitBrain is a wash — now measured three times. vs the shipped Pattern: −3.6 dmg/run on the 32-opponent legacy gauntlet (with tfil movement, docs/gauntlet_bitbrain_vs_pattern.md), +10.3 on the 15-opponent Batch-1 panel, +1.8 here on 33 opponents. All three sit inside their own MDEs; the pooled evidence is a zero. The Batch-1 +10 was a 15-opponent fluctuation.
• TMHorizon is the one arm the wider panel separates — and it loses. Its Batch-1 sign (+8.7) does not merely fail to replicate, it inverts (−10.4, 10/33, p=0.035). The damage loss is broad (24/33 opponents negative, worst Aristocles −61, Jen −54, WallAvoider −41), so it is not one outlier. Since TMHorizon was already predicted to lose by its own design docs, this is the first confirming live panel measurement of that prediction.
• Wins are flat for both arms (+0.11 / −0.03, MDEs 0.24 / 0.29): the correctors change damage at most, never survival. In this harness round wins are survival wins, so neither is a win.
• The corrector family is closed as a source of a pattern-beating gun at the resolutions tested.

Pre-registered predictions — scorecard

#	prediction	outcome
1	the +10 dmg hint does not survive the wider panel; deltas fall inside the new MDE; sign test non-significant	CORRECT (bitbrain +1.8, p=0.49; tmhorizon even reversed to −10.4, p=0.035)
2	wins remain flat	CORRECT (+0.11 / −0.03)
3	if the hint survived at p<0.05 with wins not down, it is the first gun to beat pattern	not invoked

Final direct answer for the phase (MEASURED). Across two frozen panels (15 and 33 opponents), a single frozen-binary-per-session design, 567 battles, six distinct gun configurations (five challengers + the reference), and movement pinned identically in every arm: no rack gun and no small rack beats the shipped Pattern on damage/run AND round wins. Every candidate is either not distinguishable (bitbrain, tmhorizon, rack_pk, rack_pt at n=15), a detectable loss (knn; tmhorizon at n=33), or a sub-MDE damage-only wobble (bitbrain). The shipped onlyPattern rack is CONFIRMED, not merely assumed — the gun axis's first phase ends in a measured optimum of the tested design space.

---

What to try next (rewritten AFTER Batches 1–2 — recommendations, not results)

The primary question is answered: nothing beats the shipped pattern across the frozen panel, and onlyPattern is CONFIRMED. Ranked by value per battle:

1. The damage-side hint is now CLOSED. Batch 2 (33 opponents) killed it: bitbrain is a wash (+1.8 dmg/run, p=0.49) and tmhorizon is detectably worse (−10.4 dmg/run, p=0.035). Do not spend another batch on the Pattern-lead correctors; three independent measurements of bitbrain vs Pattern now average ~0 (−3.6 / +10.3 / +1.8 dmg/run, all inside their MDEs).
2. Lead INFORMATION remains the only named gun axis (given: amplitude is dead). But the two live implementations of it (BitBrain's gain, TMHorizon's shift) are both measured negative/neutral across panels. A future axis would need a different information source, not another knob on these two — e.g. a new base prediction, or a gun-agnostic ensemble. Do not re-open the correctors.
3. The selector is confirmed negative at a 2-gun rack (rack_pt == tmhorizon; rack_pk below pattern on wins). Do not re-open it with a larger rack: the 16-gun negative already stands and Batch 1 shows the mechanism does not manufacture a win.
4. Drop knn (detectably worse on both primaries, 0/15 on damage).
5. Never chase damage without wins. This harness's round wins are survival wins, so the gun's job is to kill; a damage gain that does not raise the win rate is the ring-mover trap in a new costume (and tmhorizon's n=33 result is a negative damage signal with flat wins — also not a win).
6. Spinner-specific claim (owner's) remains UNTESTED. The legacy roster has no constant-turn spinner; SpinBot is a periodic circle-mover and is in both panels (Batch 1: bitbrain +25.3 dmg / +0 wins, tmhorizon +15.2 / +0 wins; on the 33-panel SpinBot's deltas are in the per-opponent tables). Building a true constant-turn spinner opponent is a nearly-free follow-up and is the one part of the owner's claim this campaign has not touched.

What would make us stop

PHASE STATUS (updated after Batch 2): STOPPED — the condition fired. Across Batches 1–2 no arm beats pattern beyond the MDE, and no arm shows a >= +MDE damage gain with p<0.10 (bitbrain +1.8 vs MDE 9.24; tmhorizon actually negative). The gun stage's first phase is therefore closed with "the shipped onlyPattern rack is the best gun configuration we have measured across the panels (15 and 33 opponents)" — a successful outcome, not a failure. Further gun work must open a named new axis (see What to try next), not another arm on the same axis.

• Stop the first phase once a batch's best arm cannot beat pattern beyond the MDE, or when a gun arm's damage gain is bought with a detectable win loss. At that point "onlyPattern is the measured optimum of this rack" is the conclusion, not a failure (§2 rule 4). This fired after Batch 2.
• Stop a single batch early only for a contract violation (arena not free, liveness FAIL, non-zero exit rate) — never because the numbers look boring.
• Do not invent more arms on the same axis once two consecutive batches fail to improve on pattern beyond the MDE; move to a named new axis instead (candidate list in "What to try next").

---

How to run a batch (exact commands)

# 0. wait for the arena (other campaign jobs may be fighting)
TOURNAMENT_NIMCACHE=/tmp/nc_j121 \
tools/ab/tournament_run.sh \
    --arms    tools/ab/arms_gun_b1.txt \
    --panel   tools/ab/panel_movement.txt \
    --runs 3 --rounds 3 --conc 6 --wait-arena 45 \
    --reference pattern \
    --outdir /tmp/ab/j121_g1

# Batch 2 (the wider-panel calibration) was the same command with
#   --arms tools/ab/arms_gun_b2.txt --panel tools/ab/panel_gun_b2.txt \
#   --outdir /tmp/ab/j121_g2 --wait-arena 50

# 1. the paired per-opponent table, sign tests, MDE and the pre-registered verdict
python3 tools/ab/tournament_analyze.py /tmp/ab/j121_g1 --reference pattern

--reference may be ANY arm of the session: re-analyzing an old session with a different reference is a free pairwise comparison with no battles.

Session log (outdirs are in /tmp and are NOT committed)

session	commit	battles	arms	verdict
/tmp/ab/j121_g1	1d8143a	270 (0 failed, 0 never started, 0 excluded)	pattern, bitbrain, tmhorizon, knn, rack_pk, rack_pt	nothing beats the shipped pattern; all arms not distinguishable except knn = WORSE; onlyPattern CONFIRMED
/tmp/ab/j121_g2	c343c00	297 (0 failed, 0 never started, 0 excluded)	pattern, bitbrain, tmhorizon	the Batch-1 damage hint does not survive: bitbrain +1.8 dmg/run p=0.49 (wash); tmhorizon −10.4 dmg/run p=0.035 (WORSE); wins flat

---

Phase 2: tuning the incumbent

Owner's mandate (phase 2): the phase-1 campaign closed the "other gun / other rack" design space (nothing beats the shipped Pattern; the correctors are a wash or a loss). What remains OPEN is the incumbent's own tuning: Pattern's match-length / history parameters had NEVER been swept. Phase 2 asks the direct question:

Can the shipped Pattern be improved by tuning its own match parameters — and if so, by how much on damage/run and round wins?

The lead-amplitude axis is already known dead (docs/bitbrain_campaign.md), and the radial knobs are known non-winners (job j99: bmPath structural no-op; live +0.28 pp p=0.62 for scale 0.98, −0.42 pp p=0.46 for offset −20). Those are therefore controls here, not candidates.

Task A — exposing Pattern's match-shape parameters (what and why)

MEASURED (code read). common_libs/guns/pattern_matcher.nim had exactly two tunable knobs, both RADIAL (TR_PATTERN_RAD_SCALE, TR_PATTERN_RAD_OFFSET), and neither can change the lead bearing (job j99 proved the bearing is untouched), so neither was ever the "lead information" axis. The parameters that actually control how the pattern is matched were compile-time constants:

parameter	code	what it controls	exposed as
match-key length	PatternLen = 10	the length of the movement segment compared (the search key); also how far after the match the replay starts	TR_PATTERN_LEN (int, default 10)
search depth	implicit HistorySize = 500	how far back the best-match scan may reach (scanEnd was always count−PatternLen−1)	TR_PATTERN_DEPTH (int, default 500 = full buffer)
similarity/search radius	does not exist	the search always takes the single lowest-cost match; there is no acceptance threshold or radius to expose	not exposed — nothing to expose
history buffer capacity	HistorySize = 500	the fixed array[HistorySize] backing store	runtime depth limit only; the buffer ceiling cannot be raised at runtime (see below)

Why env and not -d:. The phase-1 instrument (tools/ab/tournament_run.sh) builds ONE frozen binary from git archive HEAD and every arm differs only by its env dict. A {.intdefine.} knob would need one binary per arm, which the instrument forbids. Both new knobs are therefore resolved lazily from the environment on the first predict, exactly like the radial knobs, and default to the pre-knob constants. setMatchParams(patternLen, histDepth) is the explicit offline/unit-test twin that writes the same fields.

What could NOT be exposed cheaply (MEASURED). HistorySize sizes four fixed array[HistorySize(+1)] fields in the gun object. Raising it above 500 at runtime is impossible without a heap buffer; the runtime TR_PATTERN_DEPTH knob therefore lowers the effective search depth within the existing 500-entry buffer. A depth above 500 is clamped to 500, and a non-positive or unparsable value falls back to the shipped default. PatternLen is clamped to 1..HistorySize.

Task A — default parity (MEASURED, byte-for-byte)

• Baseline-vs-new parity dump. A throwaway harness replayed 800 ticks of tools/fixtures/drussgt_vs_crazy.jsonl through one PatternMatcherGun at all four power bins (3200 predictions) and printed every point at full precision. Compiled once against a HEAD worktree (/tmp/j123_base, before the change) and once against the modified tree: the two dumps are byte-identical (diff -q clean). The shipped default path is unchanged.
• The knobs are live and self-falling-back. TR_PATTERN_LEN=6/16 and TR_PATTERN_DEPTH=100/20 each change the dump; TR_PATTERN_LEN=banana reproduces the default dump exactly.
• Existing guards pass (no new guard tests, per the "cut ceremony" rule): common_libs/tests/test_pattern_radial_offset.nim (6 checks) and common_libs/tests/test_gun_harness.nim (all checks) pass; the env-report guard test_env_report.nim passes with TR_PATTERN_LEN / TR_PATTERN_DEPTH registered in knownEnvNames() and the effective-values report.
• Clean-archive compile is exercised by tournament_run.sh itself, which builds the frozen binary from git archive HEAD.

Task B — Batch 1 (pre-registered BEFORE any battle)

Design. One frozen binary, six env-only arms, the FROZEN 15-opponent panel tools/ab/panel_movement.txt, 3 runs × 3 rounds per (opponent, arm) = 270 battles, --conc 6, --wait-arena. Arm file: tools/ab/arms_gun_b3.txt. Reference: pattern. Movement pinned TR_MOVEMENT=strafe in every arm.

#	arm	env over the pin	what it isolates
1	pattern	(none)	the arm to beat (shipped onlyPattern rack)
2	len6	TR_PATTERN_LEN=6	shorter movement segment compared
3	len16	TR_PATTERN_LEN=16	longer movement segment compared
4	depth100	TR_PATTERN_DEPTH=100	shallower history / match search
5	rad_offset	TR_PATTERN_RAD_OFFSET=-20	control: aim 20 px short
6	rad_scale	TR_PATTERN_RAD_SCALE=0.95	control: scale the aim distance

Pre-registered prediction (written BEFORE the battles finished):

1. No arm beats pattern on both primaries. The incumbent is already tuned — the phase-2 null. The point estimates sit inside the MDE.
2. len16 is WORSE or flat on damage: a 16-tick key matches rarely in a ~500-tick buffer, so the gun falls back to the linear forecast (the weaker base) more often; wins flat.
3. len6 is flat on damage (more matches but a noisier replay) and flat on wins; possibly a sub-MDE wobble in either direction.
4. depth100 is not distinguishable from pattern — the full buffer already contains the useful candidates; a sub-MDE damage wobble is possible.
5. The two radial controls are not distinguishable and, per job j99, cannot change the real aim bearing; any damage delta is the fire-gate channel only.
6. If any surprise exists, it is a damage-only wobble without wins — the ring-mover trap — and will not be read as a win.

Pre-registered Batch-2 trigger (task rule). A Batch-1 arm is promoted to a higher-power Batch 2 only if it beats the reference pattern by the campaign rule 2 (one primary up at cross-opponent sign-test p<0.05 while the other does not go down) AND its damage CI excludes 0 AND the sign-flip permutation test gives p<0.05. Otherwise Batch 1 is the answer.

Outcome — Batch 1

MEASURED. Session /tmp/ab/j123_b1, commit 2a98aba91b0ec023f580cd2485cafba2404d275d, frozen binary sha256 287d292fb7d1…, 15 opponents × 6 arms × 3 runs × 3 rounds = 270 battles, 0 failed, 0 never started, 0 liveness exclusions. Arena serialization held: the parallel job j124 (/tmp/ab/j124_spinner.run.log) detected this session's processes at 04:08–04:18 and waited; no foreign battle ran concurrently. Every arm declared TR_MOVEMENT=strafe; the new TR_PATTERN_LEN / TR_PATTERN_DEPTH tokens appear verbatim in each overriding arm's own raw-env report and the reference arm shows the shipped defaults 10 / 500.

Pooled dashboard (all valid runs — explanation only, NOT the verdict)

arm	runs	dmg/run	dmg taken/run	wins/run	round wins	win rate	incoming hit rate	mean distance
pattern (REF)	45	101.1	161.0	1.27	57/135	42.2%	13.27%	428
len6	45	110.8	151.2	1.76	79/135	58.5%	12.28%	424
len16	45	103.3	158.8	1.53	69/135	51.1%	13.07%	427
depth100	45	99.9	154.5	1.53	69/135	51.1%	12.77%	429
rad_offset	45	107.9	157.2	1.69	76/135	56.3%	13.21%	431
rad_scale	45	105.9	157.1	1.38	62/135	45.9%	12.62%	429

Per-opponent paired deltas (arm − pattern), damage and wins

opponent	style	Δdmg_len6	Δwins_len6	Δdmg_len16	Δwins_len16	Δdmg_depth100	Δwins_depth100	Δdmg_rad_offset	Δwins_rad_offset	Δdmg_rad_scale	Δwins_rad_scale
DrussGT	dodger	+8.4	+0.67	-21.7	-0.33	+3.6	+0.67	+10.5	+1.33	+18.7	+0.67
Diamond	dodger	-22.3	+0.00	-18.1	-0.33	-54.7	-0.33	-30.9	+0.00	-17.0	-0.33
Dookious	dodger	-6.6	+1.33	+7.6	+1.00	-0.8	+0.67	+2.6	+0.67	-15.6	-0.33
GresSuffurd	dodger	+32.3	+0.00	+31.9	+0.00	-6.6	+0.00	+28.4	+0.67	-0.9	+0.00
CassiusClay	dodger	+15.0	+0.67	+6.8	+1.00	+10.0	+0.33	+12.5	+0.67	+40.4	+1.00
RetroGirl	pattern	+48.0	+1.33	+20.3	+0.67	+59.9	+1.00	+4.1	+0.00	+55.5	+0.33
TripHammer	pattern	+6.1	+0.00	+0.1	+0.33	-21.6	+0.00	-9.3	+0.00	+4.7	+0.33
Coriantumr	pattern	+1.9	-0.33	-3.9	+0.33	+2.0	+1.00	-5.3	-0.33	-10.3	-0.33
WallAvoider	wallfollower	+28.5	+1.00	-23.5	+0.00	+41.0	+0.00	+23.6	+1.00	-24.0	+0.00
HawkOnFire	cornercamper	-8.9	+0.67	-9.5	+0.00	-9.3	-0.33	-12.0	+0.33	-5.0	+0.33
SpinBot	spinner	+5.7	+0.00	+13.3	+0.00	-13.5	+0.00	-1.7	+0.00	-0.3	+0.00
DiamondStealer	rammer	-16.1	+0.00	-9.8	+0.00	-14.6	+0.00	+31.8	+1.33	+1.1	-0.67
BlitzBat	brawler	+9.1	+0.00	+17.8	+0.33	-6.3	+0.33	+9.6	+0.33	+9.2	-0.67
YersiniaPestis	aggressive	+21.0	+1.33	+2.6	+0.67	-18.6	+0.33	+27.4	+0.67	+3.0	+0.67
Ascendant	aggressive	+22.4	+0.67	+18.7	+0.33	+10.9	+0.33	+9.3	-0.33	+12.6	+0.67

Cross-opponent aggregation (the verdict layer, damage + wins)

arm	metric	mean Δ	spread (SD)	SE	95% CI	sign test (wins/n)	p(sign)	p(sign-flip)	Wilcoxon p	MDE
len6	damage	+9.63	18.97	4.90	[−0.88, +20.13]	11/15	0.1185	0.06976	0.09384	13.72
len6	wins	+0.49	0.58	0.15	[+0.17, +0.81]	8/9	0.03906	0.007812	0.01269	0.42
len16	damage	+2.18	16.62	4.29	[−7.02, +11.38]	9/15	0.6072	0.6142	0.712	12.02
len16	wins	+0.27	0.42	0.11	[+0.03, +0.50]	8/10	0.1094	0.04688	0.01852	0.30
depth100	damage	−1.24	26.52	6.85	[−15.93, +13.45]	6/15	0.6072	0.8677	0.5137	19.19
depth100	wins	+0.27	0.42	0.11	[+0.03, +0.50]	8/10	0.1094	0.04688	0.046	0.30
rad_offset	damage	+6.71	17.18	4.44	[−2.80, +16.23]	10/15	0.3018	0.1522	0.1323	12.43
rad_offset	wins	+0.42	0.54	0.14	[+0.12, +0.72]	9/11	0.06543	0.01465	0.01424	0.39
rad_scale	damage	+4.80	21.10	5.45	[−6.89, +16.49]	8/15	1	0.4095	0.6293	15.27
rad_scale	wins	+0.11	0.51	0.13	[−0.17, +0.40]	7/12	0.7744	0.5107	0.289	0.37

The pre-registered verdict (verbatim)

rank	arm	Δwins/run	Δdmg/run	sign test wins	sign test dmg	verdict (strict)	verdict (substantive)
1	len6	+0.49	+9.6	8/9 p=0.03906	11/15 p=0.1185	BETTER	BETTER
2	rad_offset	+0.42	+6.7	9/11 p=0.06543	10/15 p=0.3018	not distinguishable	not distinguishable
3	len16	+0.27	+2.2	8/10 p=0.1094	9/15 p=0.6072	not distinguishable	not distinguishable
4	depth100	+0.27	−1.2	8/10 p=0.1094	6/15 p=0.6072	not distinguishable	not distinguishable
5	rad_scale	+0.11	+4.8	7/12 p=0.7744	8/15 p=1	not distinguishable	not distinguishable

Reference pattern: 101.1 dmg/run, 1.27 wins/run, 13.27% incoming, 428 px.

Reading and the single red flag

• len6 is the only arm that beats pattern by the campaign rule — on the WINS primary: +0.49 wins/run, sign test 8/9 p=0.0391, sign-flip p=0.0078, wins CI [+0.17, +0.81] excluding 0 — while damage is nominally up (+9.6, but inside the 13.7 MDE and its CI includes 0). A 6-tick match key is broadly positive (10/15 opponents non-negative, only Coriantumr −0.33 negative).
• RED FLAG (MEASURED): all five arms are nominally positive on wins (+0.49 / +0.27 / +0.27 / +0.42 / +0.11), including rad_offset, which by job j99's exact structural proof cannot change the aim bearing and whose live effect was measured as a tie (+0.28 pp, p=0.62). The reference pattern also measures 42.2% wins here vs 50.4% in j121 on the same 15-panel (its damage is unchanged at 101–99.6), so the leading explanation for the all-arms-positive pattern is a session-level low reference, not five independent gun wins. The within-session paired deltas remain valid, but len6's win is exactly the kind of single-session effect that must replicate on a second, wider panel.
• The two shape knobs behave plausibly. len16 (fewer, more specific matches → more linear fallback) is damage-flat; depth100 (shallower search) is damage-flat at a larger MDE. Neither is a detectable win.

Pre-registered predictions — scorecard

#	prediction	outcome
1	no arm beats pattern on BOTH primaries	CORRECT (len6 beats on wins only; damage CI includes 0)
2	len16 flat/worse on damage, wins flat	PARTLY WRONG: damage flat (+2.2), wins nominally +0.27
3	len6 flat on damage and wins	WRONG: wins +0.49 significant; damage +9.6 sub-MDE
4	depth100 not distinguishable	CORRECT (damage −1.2), though wins nominally +0.27
5	radial controls not distinguishable / bearing-invariant	CORRECT: rad_scale flat; rad_offset nominal +0.42 wins but sign p=0.065 (not significant)
6	any surprise is damage-only without wins	WRONG in direction: the surprise is wins-with-nominal-damage

Batch 2 — higher-power confirmation of len6 (+ the structural control)

Why we run it (task trigger, with one recorded deviation). The task's Batch-2 trigger is: an arm beats the reference with the winning primary's CI excluding 0 AND sign-flip p<0.05. len6 satisfies it on wins (CI [+0.17, +0.81]; p(sign-flip)=0.0078). Deviation, recorded: the Batch-1 pre-registration added a stricter clause — "its damage CI excludes 0" — which len6's damage ([−0.88, +20.13]) does not meet. We run Batch 2 anyway because (a) the task rule keys on the winning primary and (b) the all-arms-positive red flag means a replication is the only way to tell a real len6 effect from a session-level reference anomaly. This is a deviation from the letter of my own pre-registration, not from the task's criterion.

Design. One frozen binary, four env-only arms, the wider panel tools/ab/panel_gun_b2.txt (33 opponents, superset of Batch 1's 15), 3 runs × 3 rounds = 396 battles, --conc 6, --wait-arena. Arm file: tools/ab/arms_gun_b4.txt. Reference: pattern. Movement pinned TR_MOVEMENT=strafe in every arm.

#	arm	env over the pin	role
1	pattern	(none)	reference
2	len6	TR_PATTERN_LEN=6	the candidate
3	len16	TR_PATTERN_LEN=16	dose-response on key length
4	rad_offset	TR_PATTERN_RAD_OFFSET=-20	structural positive control (bearing-invariant)

Pre-registered prediction (written BEFORE the battles finished):

1. len6's +0.49 wins does NOT replicate. On 33 opponents its wins delta collapses toward the MDE and the sign test (or the sign-flip test) fails. Rationale: all five Batch-1 arms were positive on wins including the bearing-invariant rad_offset, and the reference was 8 points low on win rate versus j121's same-panel measurement — a single-session low reference, not a len6 effect.
2. rad_offset is not a detectable win; if it, too, replicates a wins gain, the wins axis is being moved by something other than the aim bearing and the whole Batch-1 wins signal is an artifact.
3. len16 stays within its MDE on both primaries.
4. Damage stays within the MDE for every arm.
5. If len6 DOES replicate (winning-metric CI excludes 0, sign-flip p<0.05, damage not detectably down), it is recorded as the campaign's champion candidate — and the shipped-default flip remains a separate, explicit decision that is NOT taken in this job.

Outcome — Batch 2

MEASURED. Session /tmp/ab/j123_b2, commit 1b59b6581075cf4019773dd74e6db9eecf2fcb02, frozen binary sha256 8155c39fbc6a…, 33 opponents × 4 arms × 3 runs × 3 rounds = 396 battles, 0 failed, 0 never started, 0 liveness exclusions. Arena serialization held: the job waited at the start of the run for j124's spinner fleet (/tmp/ab/j124_spinner) and only started once it was gone; no foreign battle ran concurrently with the measurement. Every arm declared TR_MOVEMENT=strafe; TR_PATTERN_LEN / TR_PATTERN_RAD_OFFSET appear verbatim in each overriding arm's raw-env report.

Pooled dashboard (all valid runs — explanation only, NOT the verdict)

arm	runs	dmg/run	dmg taken/run	wins/run	round wins	win rate	incoming hit rate	mean distance
pattern (REF)	99	129.5	124.4	2.11	209/297	70.4%	12.54%	428
len6	99	131.4	121.0	2.07	205/297	69.0%	12.04%	423
len16	99	125.8	121.4	2.04	202/297	68.0%	12.36%	426
rad_offset	99	126.9	132.4	1.91	189/297	63.6%	13.03%	425

Per-opponent paired deltas (arm − pattern), damage and wins

opponent	style	Δdmg_len6	Δwins_len6	Δdmg_len16	Δwins_len16	Δdmg_rad_offset	Δwins_rad_offset
Aristocles	dodger	+0.7	+0.00	-12.7	+0.00	-5.3	+0.00
Ascendant	other	+13.8	-0.67	-23.1	-1.33	+0.7	-1.00
BlitzBat	regular	-2.6	+0.00	+4.4	+0.33	-12.0	+0.33
BrokenSword	other	-17.7	+0.00	+6.0	+0.33	-15.9	+0.33
CassiusClay	dodger	+3.7	+0.67	-7.5	+0.00	+32.4	-0.33
Cigaret	dodger	-26.3	-2.00	-5.1	-0.33	-29.1	-1.67
CigaretBH	dodger	+17.6	+0.33	+1.1	+0.33	+18.2	+0.00
Coriantumr	other	-3.9	+0.00	-14.1	-0.33	+3.9	+0.00
Diamond	dodger	-5.2	-0.33	-8.8	-0.67	-13.7	-0.67
DiamondHawk	other	+3.2	-0.33	-3.9	+0.00	-6.6	-0.33
DiamondStealer	regular	+29.5	+1.00	+27.4	+0.33	+16.5	+0.33
Dookious	dodger	+16.6	+0.33	+14.5	+0.33	-2.1	+0.00
DrussGT	other	-13.2	+0.00	+20.7	+0.33	-15.9	-0.33
FloodMini	regular	+1.0	+0.00	+12.0	+0.00	+20.7	+0.00
GresSuffurd	dodger	+10.8	+0.33	-11.1	+0.00	+4.8	+0.00
HawkOnFire	regular	+24.9	+0.67	+26.3	-0.33	-2.6	+0.67
Jen	dodger	-36.3	+0.00	-27.0	+0.00	-16.1	-0.33
Komarious	dodger	+3.3	+0.33	+1.2	+0.00	-11.4	+0.33
KurtWaveSurfer	dodger	-18.9	-0.67	-35.9	+0.00	-7.8	+0.00
LightningBug	other	-15.3	+0.00	-10.7	+0.00	-20.7	+0.00
LionWWSVMvoid	dodger	+19.1	+0.00	-1.3	+0.00	-1.7	+0.00
Lukious	dodger	+17.6	+0.00	+1.8	+0.33	+19.6	+0.33
PatternRobot	regular	+21.3	+0.00	+6.7	+0.00	-1.3	+0.00
Phoenix	other	-8.2	+0.33	-29.5	-0.33	-4.4	-0.67
RetroGirl	other	-29.6	-0.33	-6.7	+0.00	-17.0	-1.67
RougeDC	dodger	+7.5	+0.00	-1.9	-0.33	+2.3	+0.00
Shadow	other	+3.1	-0.67	-10.9	-0.67	-10.4	-0.67
SpinBot	spinner	-14.7	+0.00	-9.5	+0.00	-3.5	+0.00
TripHammer	other	+0.9	-0.33	-7.6	-0.33	-16.8	-1.00
WallAvoider	regular	+35.7	-0.33	+3.3	+0.33	-5.6	-1.00
WaveSurferGF	dodger	+12.5	+0.33	-16.5	-0.67	+26.3	+0.33
WaveSurferPG	dodger	-1.2	-0.67	+0.3	+0.33	-22.7	+0.00
YersiniaPestis	other	+10.8	+0.67	-4.7	+0.00	+8.6	+0.33

Cross-opponent aggregation (the verdict layer, damage + wins)

arm	metric	mean Δ	spread (SD)	SE	95% CI	sign test (wins/n)	p(sign)	p(sign-flip)	Wilcoxon p	MDE
len6	damage	+1.83	17.09	2.98	[−4.00, +7.67]	20/33	0.2962	0.5417	0.4859	8.34
len6	wins	−0.04	0.54	0.09	[−0.22, +0.14]	10/20	1	0.7631	0.8806	0.26
len16	damage	−3.72	14.45	2.52	[−8.65, +1.22]	13/33	0.2962	0.1494	0.09657	7.05
len16	wins	−0.07	0.38	0.07	[−0.20, +0.06]	9/19	1	0.379	0.5303	0.19
rad_offset	damage	−2.69	14.72	2.56	[−7.72, +2.33]	11/33	0.08014	0.2997	0.1952	7.18
rad_offset	wins	−0.20	0.56	0.10	[−0.39, −0.01]	8/20	0.5034	0.05926	0.05875	0.28

The pre-registered verdict (verbatim)

rank	arm	Δwins/run	Δdmg/run	sign test wins	sign test dmg	verdict (strict)	verdict (substantive)
1	len6	−0.04	+1.8	10/20 p=1	20/33 p=0.2962	not distinguishable	not distinguishable
2	len16	−0.07	−3.7	9/19 p=1	13/33 p=0.2962	not distinguishable	not distinguishable
3	rad_offset	−0.20	−2.7	8/20 p=0.5034	11/33 p=0.08014	not distinguishable	not distinguishable

Reference pattern: 129.5 dmg/run, 2.11 wins/run, 12.54% incoming, 428 px.

Reading

• len6's Batch-1 wins win did not replicate. On 33 opponents it collapses from +0.49 wins/run to −0.04 wins/run (10/20, p=1) and from +9.6 to +1.8 dmg/run (20/33, p=0.30, CI [−4.00, +7.67], MDE 8.34). Both primaries are squarely inside the MDE. Verdict: NOT DISTINGUISHABLE.
• The Batch-1 red flag is explained. All five Batch-1 arms were wins-positive including the bearing-invariant rad_offset; here rad_offset turns negative on both primaries (−0.20 wins, −2.7 dmg) and the other two arms are wins-flat. The Batch-1 effect was a session-level low reference: pattern measured 42.2% win rate on 15 opponents in Batch 1, versus 70.4% here on its 33-opponent superset and 63.3% in j121 Batch 2 on the same 33-panel. A single-session paired comparison is internally valid, but a wins-only signal in one session is not evidence until it replicates — which is exactly what Batch 2 tested.
• The dose-response is flat and slightly negative for longer keys. len16 is −3.7 dmg/run and −0.07 wins/run (damage sign test p=0.30; if anything it drifts toward the linear fallback as predicted in Batch 1).
• No shipped default was touched; this job is a measurement.

Pre-registered predictions — scorecard

#	prediction	outcome
1	len6's +0.49 wins does not replicate; delta collapses toward the MDE	CORRECT (+0.49 → −0.04 wins, p=1; damage +9.6 → +1.8)
2	rad_offset is not a detectable win	CORRECT (it is nominally negative: −0.20 wins, −2.7 dmg)
3	len16 stays within its MDE on both primaries	CORRECT (−3.7 dmg vs MDE 7.05; −0.07 wins)
4	damage stays within the MDE for every arm	CORRECT
5	if len6 replicates it is the champion candidate	not invoked

Phase 2 — final direct answer

MEASURED (two sessions, 15 then 33 opponents, 666 battles, 6 frozen-binary arms + the reference): NO — the shipped Pattern cannot be improved by tuning its own match-length or history parameters at the resolution we can measure. The incumbent is already tuned on this axis.

• The one Batch-1 signal (len6, +0.49 wins/run on 15 opponents, sign p=0.039, sign-flip p=0.008) reversed to a wash on 33 opponents (−0.04 wins/run, p=1; +1.8 dmg/run, p=0.30). It was a session-level low reference, not a gun effect.
• On damage/run and round wins, the best Batch-2 challenger is inside its MDE on both primaries (len6: +1.8 dmg/run vs MDE 8.34, −0.04 wins/run vs MDE 0.26). Longer keys (len16) and a shallower search (depth100) do not help.
• The two pre-existing radial knobs remain what j99 measured: bearing-invariant and not winners; in Batch 2 rad_offset is nominally negative.
• No shipped default changed. Exposing the knobs (TR_PATTERN_LEN, TR_PATTERN_DEPTH) does not change the default path — proven byte-identical before any battle.

(MEASURED vs INFERRED. The knob exposure, the byte-identity parity dump, the 270- and 396-battle sessions, every per-opponent delta, the CIs, MDEs, sign tests and sign-flip tests above are all MEASURED. The "incumbent is already tuned" reading is a MEASURED null at these resolutions; any claim that no setting whatsoever could ever help would be INFERRED and is deliberately not made.)

What to try next (rewritten AFTER Phase 2)

The phase-1 conclusion stands and is now joined by the phase-2 one:

1. The match-shape axis is CLOSED. Match-key lengths 6 and 16 and a shallow (100-tick) history search do not beat the shipped defaults (10, full 500). Do not spend another batch on TR_PATTERN_LEN / TR_PATTERN_DEPTH unless a specific mechanism is named; the MDE is ~8 dmg/run and ~0.26 wins/run, so only a very large effect could even be seen.
2. TR_MOVEMENT=strafe + default Pattern is the measured optimum of the tested design space, and Pattern is now measured-tuned on its own parameters as well.
3. The named open axes remain the ones phase 1 named: a different information source for the lead (not another knob on BitBrain/TMHorizon, both measured negative/neutral), and the owner's spinner-specific claim (j124 is now on it). The lead-amplitude axis and the radial axis stay dead.
4. Session-level reference variance is large and must be respected. The same frozen reference on the same movement measured 42.2% wins (Batch 1, 15 opponents) and 70.4% wins (Batch 2, 33 opponents, superset). Any wins-only signal from one session must be replicated before it is believed — this job's Batch-1 len6 is the second campaign example (after j121's bitbrain damage hint) of a single-session wobble dying on replication.

Session log (Phase 2 rows appended)

session	commit	battles	arms	verdict
/tmp/ab/j123_b1	2a98aba	270 (0 failed, 0 never started, 0 excluded)	pattern, len6, len16, depth100, rad_offset, rad_scale	len6 the only rule-2 win (wins +0.49, sign p=0.039); red flag: all 5 arms wins-positive incl. the bearing-invariant rad_offset
/tmp/ab/j123_b2	1b59b65	396 (0 failed, 0 never started, 0 excluded)	pattern, len6, len16, rad_offset	len6 does not replicate (−0.04 wins, p=1; +1.8 dmg, p=0.30); all arms not distinguishable; the incumbent is already tuned

---

Allocation: is the selector leaving value on the table?

Question (owner-spotted, 2026-09-26). The selector's own /tmp/gun_stats.jsonl (10,608 rounds, 2-gun racks, selector ON) gives Pattern ~66% of selection ticks and that looks justified by per-shot hit rate. But GUN_SELECTOR_FLOOR is a FITNESS floor (only ignores a gun below 25% of the best), not a SHARE floor: nothing guarantees the second gun any share of the shots. The ~66/34 split is an OUTCOME of ranking + hysteresis, not a POLICY. Nobody has ever tested whether a deliberately different split beats pattern alone. This batch builds the mechanism (TR_RACK_SHARE, default-off) and asks directly:

Is gun ALLOCATION a lever?

Pre-registration (written BEFORE the batch)

• Mechanism. TR_RACK_SHARE=pattern:50,bitbrain:50 (relative weights, case-insensitive RackGunNames) replaces chooseFromFit's ranking with a deterministic deficit round-robin over the named ADMITTED guns. Each allocation is held for GUN_SELECTOR_DWELL ticks (turret convergence) so the share is over dwell epochs; selected-tick counts follow the weights. Deterministic (not randomized) because the question is whether a specified split is better, the schedule is auditable, and it needs no seed.
• Default-OFF parity. Unset TR_RACK_SHARE leaves the weights empty and selectGun takes the unchanged ranking path. Parity proven before fighting: test_gun_harness 39, test_rack_membership 48, test_selector_tiebreak 19, test_env_report 25 — all green at their exact shipped counts.
• Panel. tools/ab/panel_movement.txt — the frozen 15-opponent movement panel (never edited). Unit of evidence = number of opponents.
• Arms (tools/ab/arms_alloc.txt, 6 arms): pattern (reference, shipped); sel_pb (selector ON, Pattern+BitBrain, shipped policy = the ~66/34 OUTCOME); share_5050_pb; share_7030_pb; share_5050_pt (TMHorizon); share_5050_pk (KNN). Movement pinned TR_MOVEMENT=strafe in every arm.
• Judge on damage/run and ROUND WINS (standing rule); hit rate and distance are explanation. Per-opponent deltas vs the reference; CI, sign test, sign-flip permutation, MDE.
• Decision rule (pre-registered).
  1. If a forced-share arm beats pattern (CI excluding 0 and sign-flip p<0.05) → ALLOCATION IS A LEVER; the selector was leaving value on the table and the next job tunes the share.
  2. If no forced-share arm beats pattern → the ~66/34 allocation was already right; the rack question is genuinely CLOSED.
  3. Either way, report whether the forced arms differ from sel_pb — that isolates policy from gun choice.
• Allocation evidence. Per arm, the applied share (from each run's gun_stats.jsonl selected counts) and each gun's per-shot hit rate (realShots/realHits, same battles). Per-shot hit rate is the right signal HERE because the movement is identical inside a battle.

RESULTS

Session /tmp/ab/j127_alloc2, commit 2a3a62a, frozen binary sha256 1b663dbbd365…, 15 opponents × 6 arms × 3 runs × 3 rounds = 270 battles, 0 failed, 0 never started, 0 liveness exclusions (827 s wall). Analyzer: tools/ab/tournament_analyze.py.

Mechanism bug found and fixed before the ledger run (MEASURED). The first session (/tmp/ab/j127_alloc) exposed that bot.tick RESETS to 0 each round while tracker.currentSince persists, so the dwell hold (tick - currentSince) < DWELL went negative and LOCKED the round-1-end gun for every later round (per-round applied share was [50, 100, 100] instead of [50, 50, 50]). The share path now requires tick >= currentSince (commit 2a3a62a); the shipped ranking path is untouched. The same latent lock exists in the shipped selector's hysteresis for any multi-gun rack — the sel_pb arm's per-round share is likewise bimodal (e.g. [98, 100], [91, 0, 51]), which is why its aggregate ~69/31 is itself a round-boundary artifact, not a stable policy. This is a MEASURED property of the shipped mechanism, not fixed here (no shipping).

Applied share and per-gun per-shot hit rate (MEASURED, per-run gun_stats.jsonl). All 45 runs per forced arm print TR_RACK_SHARE active; 0 errors, 0 unrecognized. The forced shares land on target (50.1/49.9, 70.0/30.0). Per-shot hit rate is realHits/realShots summed over the same battles.

arm	applied share (selected ticks)	shots	per-gun per-shot hit
pattern	Pattern 100.0%	7016	Pattern 15.94%
sel_pb (shipped policy)	Pattern 69.4% / BitBrain 30.6%	4470 / 2024	Pattern 19.08% / BitBrain 12.85%
share_5050_pb	Pattern 50.1% / BitBrain 49.9%	3034 / 3042	Pattern 17.77% / BitBrain 14.14%
share_7030_pb	Pattern 70.0% / BitBrain 30.0%	4405 / 1877	Pattern 17.68% / BitBrain 16.36%
share_5050_pt	Pattern 50.1% / TMHorizon 49.9%	3404 / 3407	Pattern 18.18% / TMHorizon 15.59%
share_5050_pk	Pattern 50.1% / KNN 49.9%	3164 / 2633	Pattern 17.98% / KNN 12.53%

Per-opponent results (Δdmg/run / Δwins/run, arm − pattern).

opponent	sel_pb	share_5050_pb	share_7030_pb	share_5050_pt	share_5050_pk
DrussGT	+26.5 / +0.67	-36.8 / -0.67	-10.3 / -0.33	-1.1 / -0.33	-5.1 / +0.33
Diamond	+7.6 / +0.33	-4.1 / -0.33	-15.0 / +0.00	+12.2 / -0.33	-6.3 / -0.33
Dookious	+5.0 / +0.00	-12.6 / -0.33	-13.7 / -0.33	-12.9 / -0.67	-13.9 / +0.00
GresSuffurd	+29.7 / +0.33	-3.0 / -0.33	+16.5 / -0.67	+23.6 / +0.00	-11.4 / -0.67
CassiusClay	+25.7 / +0.33	+33.0 / +0.33	+21.4 / +0.67	+29.5 / +0.67	-7.5 / +0.00
RetroGirl	+13.5 / +1.33	-19.6 / +1.00	+7.7 / +0.67	+73.7 / +2.00	+20.4 / +0.67
TripHammer	+12.9 / +0.33	+1.1 / +0.33	+4.8 / +0.67	-6.8 / +0.33	+1.2 / +0.00
Coriantumr	-1.9 / -0.33	-25.7 / -0.67	-16.9 / +0.33	-13.3 / -1.33	-44.9 / -1.67
WallAvoider	-31.8 / +1.00	+28.9 / +1.33	+9.0 / +1.00	-8.2 / +1.00	-27.7 / -0.33
HawkOnFire	+0.2 / -1.33	+4.7 / -0.33	+37.6 / +0.00	-9.3 / -0.33	-41.2 / -2.00
SpinBot	-14.7 / +0.00	+12.7 / +0.00	+6.0 / +0.00	+16.0 / +0.00	-15.3 / +0.00
DiamondStealer	+27.4 / +0.00	+16.0 / +0.67	-24.1 / -0.33	-4.3 / +0.00	+8.9 / +0.67
BlitzBat	+3.5 / +0.33	+26.3 / +0.00	+10.2 / +0.33	+11.1 / +0.33	+10.6 / +0.00
YersiniaPestis	-18.5 / -1.33	-15.9 / -0.67	-11.9 / -0.67	+4.4 / -0.33	-0.3 / -1.00
Ascendant	-0.0 / +0.00	-5.3 / -0.33	+31.4 / +1.67	-6.5 / +0.33	-33.1 / -0.33

Cross-opponent tests/CI/MDE vs pattern (the verdict layer). Primary metrics only; p is the exact sign-flip permutation on the per-opponent mean.

arm	metric	mean Δ	95% CI	sign test	p(sign-flip)	MDE	verdict
sel_pb	damage	+5.68	[-4.29, +15.64]	10/15	0.2393	13.01	not distinguishable
sel_pb	wins	+0.11	[-0.29, +0.51]	8/11	0.6387	0.52	not distinguishable
share_5050_pb	damage	-0.02	[-11.41, +11.36]	7/15	0.9968	14.87	not distinguishable
share_5050_pb	wins	-0.00	[-0.34, +0.34]	5/13	1	0.45	not distinguishable
share_7030_pb	damage	+3.50	[-6.73, +13.74]	9/15	0.4725	13.37	not distinguishable
share_7030_pb	wins	+0.20	[-0.16, +0.56]	7/12	0.3193	0.47	not distinguishable
share_5050_pt	damage	+7.21	[-5.37, +19.80]	7/15	0.2582	16.44	not distinguishable
share_5050_pt	wins	+0.09	[-0.34, +0.52]	6/12	0.7539	0.56	not distinguishable
share_5050_pk	damage	-11.03	[-21.54, -0.52]	4/15	0.04205	13.72	WORSE (damage)
share_5050_pk	wins	-0.31	[-0.73, +0.11]	3/10	0.1777	0.55	not distinguishable

Policy isolation — forced arms vs sel_pb (MEASURED, --reference sel_pb). This is the arm that holds gun choice fixed and asks whether the POLICY (ranking vs forced schedule) changes anything. share_7030_pb deliberately reproduces sel_pb's applied share (70.0/30.0 vs 69.4/30.6), so it is the cleanest test.

arm	metric	mean Δ	95% CI	sign test	p(sign-flip)	MDE
share_7030_pb	damage	-2.17	[-16.90, +12.55]	6/15	0.7542	19.23
share_7030_pb	wins	+0.09	[-0.34, +0.52]	6/12	0.7432	0.56
share_5050_pb	damage	-5.70	[-21.93, +10.54]	6/15	0.4659	21.20
share_5050_pb	wins	-0.11	[-0.44, +0.22]	4/12	0.5771	0.43
share_5050_pt	damage	+1.54	[-12.09, +15.16]	7/15	0.8182	17.80
share_5050_pt	wins	-0.02	[-0.37, +0.33]	5/10	1	0.46
share_5050_pk	damage	-16.71	[-27.92, -5.50]	4/15	0.00769	14.64
share_5050_pk	wins	-0.42	[-0.73, -0.11]	2/13	0.01733	0.40

Pooled dashboard (descriptive, not the verdict): pattern 101.9 dmg/1.47 wins; sel_pb 107.5/1.58; share_5050_pb 101.8/1.47; share_7030_pb 105.4/1.67; share_5050_pt 109.1/1.56; share_5050_pk 90.8/1.16.

VERDICT

DIRECT ANSWER (MEASURED): NO — gun ALLOCATION is not a lever on the frozen 15-opponent panel at this resolution. No forced-share arm beats pattern alone by the pre-registered rule (CI excluding 0 AND sign-flip p<0.05). The selector's ~66/34 split was already right within the MDE; the rack question is genuinely CLOSED.

• The best forced arm is share_7030_pb (applied 70/30, i.e. re-creating the observed ~66/34 split deliberately): +0.20 wins/run, +3.5 dmg/run vs pattern, both inside their MDEs (0.47 wins, 13.4 dmg), sign-flip p=0.32 / 0.47. A nominal, non-significant lean toward the incumbent's own split.
• The deliberate 50/50 arms gain nothing (share_5050_pb ≈ 0/0) or cost damage (share_5050_pt +7.2 dmg but +0.09 wins, not distinguishable).
• The only DETECTABLE allocation effect is NEGATIVE: forcing 50/50 with KNN is detectably WORSE on damage vs pattern (−11.0, CI excludes 0, p=0.042) and detectably worse than sel_pb on BOTH wins and damage (−0.42 wins, p=0.017; −16.7 dmg, p=0.008). Allocation can HURT; it cannot help here.
• policy vs gun choice (MEASURED). Forcing the selector's own applied share (share_7030_pb ≈ sel_pb) is not distinguishable on either primary, so at the same allocation the ranking-vs-forced policy makes no measurable difference. sel_pb itself is nominally positive (+0.11 wins, +5.7 dmg) but not distinguishable — this session's reference is a low one (48.9% wins), consistent with the campaign's known session-level reference variance.
• Caveat that strengthens the finding (MEASURED). The applied share of the shipped selector is not a stable policy at all: its round-boundary dwell lock makes per-round shares bimodal (a gun can hold 100% of a round). The forced arms, with the fix, are the first clean allocation measurement — and they show no upside to deviating from Pattern-dominant.

MEASURED: the allocator code + default-OFF parity (39/48/19/25), the round-boundary bug and its fix, all 4 forced arms' applied shares (exactly 50/50 and 70/30) and per-gun per-shot hit rates, the 270-battle session, every per-opponent delta, CI, MDE, sign and sign-flip test, and the policy-isolation comparison. INFERRED: that no share schedule whatsoever could ever help (this batch bounds only the shares it tested, at this MDE and panel).

---

Cross-reference: the ADE+SBC gun (rack id 17) is RETIRED

The bitbrain arm named in earlier batches of this ledger is NOT the gun shipped at id 16. The ADE+SBC gun that briefly held the BITBRAIN rack name and the TR_BITBRAIN_* env prefix at rack id 17 was retired and removed from the tree (owner: "not learning, i watched it, throw it away and we forget about it"). Its tombstone, evidence and removal list are in docs/bitbrain_campaign.md §RETIRED. The bitbrain verdict in this ledger — nothing beat Pattern — is unchanged; this line only records that the id-17 experiment that followed it is closed, so the two ledgers do not contradict each other. The surviving "BitBrain-named" capability is the id-16 lead-gain corrector, now called LEADGAIN.