{"id":"W4247440864","doi":"10.1353/lac.2015.0019","title":"Playing Checkers with Machines—from Ajeeb to Chinook","year":2015,"lang":"en","type":"article","venue":"Information & Culture","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Champion; Chinook wind; Automaton; History; Operations research; Engineering; Political science; Computer science; Law; Artificial intelligence; Fish <Actinopterygii>; Fishery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008123178,0.000555241,0.0002072069,0.001044633,0.003581803,0.004844515,0.0008936253,0.001097532,0.01019674],"category_scores_gemma":[0.00396821,0.0003617728,0.0002944354,0.0008564917,0.004833388,0.006602189,0.003210616,0.002126878,0.001935522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002647914,"about_ca_system_score_gemma":0.002002993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0171397,"about_ca_topic_score_gemma":0.02829785,"domain_scores_codex":[0.9992486,0.0001553946,0.00003959353,0.0001635001,0.0002675898,0.0001253654],"domain_scores_gemma":[0.9990854,0.0002730742,0.00004644787,0.000118257,0.0002501073,0.0002266956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006309105,0.0001943902,0.004094982,0.00043109,0.00005267336,0.0005123492,0.01538671,0.001137244,0.008979917,0.5163832,0.1325108,0.3196857],"study_design_scores_gemma":[0.00004860082,0.0001251737,0.003034413,0.0003586159,0.00002922729,0.0003741469,0.003270152,0.002257451,0.003584906,0.09289934,0.8939351,0.00008286633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1686122,0.02455336,0.03465413,0.04873047,0.004459731,0.000177231,0.0004216795,0.002548738,0.7158425],"genre_scores_gemma":[0.7561415,0.01117405,0.03768089,0.01130189,0.000799102,0.0002064887,0.0004499088,0.001332437,0.1809136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0171397,"threshold_uncertainty_score":0.0341115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02681013905703501,"score_gpt":0.2662183340392502,"score_spread":0.2394081949822152,"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."}}