FuryBench Testing Framework

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Active : 31 Machines / 500 Threads / 237.7 MNPS
Priority 0
PlentyChess Yoshie2000diff40.0+0.40
ELO    1.08 +- 1.58 (95%)
LLR    0.88 (-2.25, 2.89) [0.00, 2.50]
GAMES  N: 41970 W: 10084 L: 9954 D: 21932
PENTA  [3, 4663, 11526, 4787, 6]
Quanticade DarkNeutrino
search.c: Correction margin to futility pruning
diff60.0+0.60
ELO    -0.23 +- 2.04 (95%)
LLR    -1.21 (-2.25, 2.89) [0.00, 3.00]
GAMES  N: 24598 W: 5618 L: 5634 D: 13346
PENTA  [6, 2702, 6897, 2690, 4]
Finished
Caissa Witek
Search: Fitted 50-move eval damping Replace the linear (234 - hmc) / 234 eval damping with a curve fitted on game results: 1 - 0.221 x - 0.713 x^2 with x = hmc / 100, and 1 - x for pawnless positions. The multipliers are a table built at startup (indexed by pawnless and half-move counter), so the search does one lookup, a multiply and a shift. Fit: for each half-move-counter bucket, the slope k of the logistic E(k * eval) that best predicts the game result, relative to HMC 0-7, using the raw static eval of the master net. 69M positions from OpenBench STC games, 2.1M from LTC games and 13.6M from selfplay data give nearly the same curve (multiplier at HMC 48: 0.70 / 0.61 / 0.71, at HMC 80: 0.36 / 0.32 / 0.40; previously 0.79 and 0.66). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
diff10.0+0.10
ELO    -5.90 +- 2.77 (95%)
LLR    -2.95 (-2.94, 2.94) [0.00, 2.00]
GAMES  N: 13024 W: 3025 L: 3246 D: 6753
PENTA  [1, 1510, 3714, 1283, 4]
PlentyChess Yoshie2000diff8.0+0.08
ELO    0.91 +- 0.69 (95%)
LLR    2.89 (-2.25, 2.89) [0.00, 2.50]
GAMES  N: 243308 W: 59420 L: 58786 D: 125102
PENTA  [334, 28319, 63719, 28943, 339]
Quanticade DarkNeutrino
search.c: Fix capture history indexing on enpassant
diff10.0+0.10
ELO    1.11 +- 2.02 (95%)
LLR    2.97 (-2.94, 2.94) [-3.00, 1.00]
GAMES  N: 27626 W: 6597 L: 6509 D: 14520
PENTA  [62, 3065, 7470, 3155, 61]
PlentyChess Yoshie2000diff8.0+0.08
ELO    -0.71 +- 1.68 (95%)
LLR    -2.26 (-2.25, 2.89) [0.00, 2.50]
GAMES  N: 40756 W: 9879 L: 9962 D: 20915
PENTA  [56, 4850, 10644, 4777, 51]
PlentyChess Yoshie2000diff8.0+0.08
ELO    -1.39 +- 2.06 (95%)
LLR    -2.26 (-2.25, 2.89) [0.00, 2.50]
GAMES  N: 26998 W: 6571 L: 6679 D: 13748
PENTA  [61, 3188, 7081, 3136, 33]
PlentyChess Yoshie2000diff8.0+0.08
ELO    -9.34 +- 4.59 (95%)
LLR    -2.26 (-2.25, 2.89) [0.00, 2.50]
GAMES  N: 5468 W: 1255 L: 1402 D: 2811
PENTA  [13, 707, 1437, 568, 9]
Quanticade DarkNeutrino
search.c: Correction margin to futility pruning
diff10.0+0.10
ELO    0.10 +- 1.50 (95%)
LLR    -1.63 (-2.25, 2.89) [0.00, 3.00]
GAMES  N: 50666 W: 11967 L: 11952 D: 26747
PENTA  [90, 5886, 13355, 5923, 79]
Quanticade DarkNeutrino
see.c: Fix SEE pinned ray
diff10.0+0.10
ELO    -0.13 +- 0.95 (95%)
LLR    2.94 (-2.94, 2.94) [-3.00, 1.00]
GAMES  N: 121730 W: 28838 L: 28884 D: 64008
PENTA  [223, 13521, 33428, 13465, 228]
Quanticade DarkNeutrino
Adv datagen vs SF 6000 fixed nodes
time odds diffN=5000
ELO    -5.38 +- 0.19 (95%)
GAMES  N: 10000006/10000000 W: 3782460 L: 3937423 D: 2280123
Quanticade DarkNeutrino
Switch to 16K history limits
diff10.0+0.10
ELO    -1.95 +- 1.94 (95%)
LLR    -2.97 (-2.94, 2.94) [-3.00, 1.00]
GAMES  N: 31132 W: 7316 L: 7491 D: 16325
PENTA  [61, 3801, 8003, 3654, 47]
PlentyChess Yoshie2000diff40.0+0.40
ELO    1.09 +- 0.89 (95%)
LLR    2.89 (-2.25, 2.89) [0.00, 2.50]
GAMES  N: 133196 W: 32346 L: 31928 D: 68922
PENTA  [24, 14692, 36740, 15126, 16]
Integral Furydiff10.0+0.10
ELO    -1.58 +- 2.41 (95%)
LLR    -2.27 (-2.25, 2.89) [0.00, 3.00]
GAMES  N: 19356 W: 4719 L: 4807 D: 9830
PENTA  [36, 2248, 5191, 2174, 29]
Integral Furydiff10.0+0.10
ELO    -0.67 +- 1.89 (95%)
LLR    -2.30 (-2.25, 2.89) [0.00, 3.00]
GAMES  N: 32628 W: 8017 L: 8080 D: 16531
PENTA  [59, 3872, 8543, 3753, 87]
Integral Furydiff10.0+0.10
ELO    -0.51 +- 1.75 (95%)
LLR    -2.40 (-2.25, 2.89) [0.00, 3.00]
GAMES  N: 38510 W: 9502 L: 9558 D: 19450
PENTA  [68, 4613, 9968, 4519, 87]
PlentyChess Yoshie2000diff40.0+0.40
ELO    -3.67 +- 2.96 (95%)
LLR    -2.26 (-2.25, 2.89) [0.00, 2.50]
GAMES  N: 12316 W: 2976 L: 3106 D: 6234
PENTA  [7, 1466, 3343, 1334, 8]