{"id":"W1947291763","doi":"10.48550/arxiv.1412.6564","title":"Move Evaluation in Go Using Deep Convolutional Neural Networks","year":2014,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Monte Carlo tree search; Computer science; Convolutional neural network; Artificial intelligence; Deep learning; Machine learning; Monte Carlo method","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005229742,0.0001062848,0.0001086459,0.0001423569,0.0001063215,0.0000494413,0.0005730432,0.00007489193,0.00003928393],"category_scores_gemma":[0.000088381,0.0001267683,0.00005187733,0.0006720696,0.0000935722,0.0006578696,0.0001792983,0.0001432766,0.00004861346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002152541,"about_ca_system_score_gemma":0.00004696463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001321738,"about_ca_topic_score_gemma":0.0001741285,"domain_scores_codex":[0.9988466,0.0002202717,0.0001460413,0.000418115,0.0001022885,0.0002666824],"domain_scores_gemma":[0.9992035,0.0001512803,0.0000846594,0.0003452561,0.0001435684,0.00007172158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006122077,0.0000201017,0.0111598,9.46776e-7,0.000003462029,0.000008616783,0.00008117324,0.8539724,0.00002962234,0.1295309,0.00000904753,0.005177804],"study_design_scores_gemma":[0.0001278114,0.00002130944,0.004967539,0.000007251708,0.000008432777,0.000002860443,0.00004222302,0.9674386,0.00006855145,0.02714441,0.00003477848,0.000136174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3898443,0.0000173781,0.6091539,0.00002865636,0.0002269967,0.00007985035,1.542621e-7,0.00003714472,0.0006116225],"genre_scores_gemma":[0.9983731,0.000003092377,0.001359097,0.0001256421,0.00006857337,3.287389e-7,0.000001517766,0.000005243631,0.00006343165],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6085287,"threshold_uncertainty_score":0.516946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116652315484495,"score_gpt":0.227260463415021,"score_spread":0.1155952318665715,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}