{"id":"W1501727541","doi":"10.1016/s0065-2458(00)80019-4","title":"The games computers (and people) play","year":2000,"lang":"en","type":"book-chapter","venue":"Advances in computers","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Successor cardinal; Bridge (graph theory); Computer science; Multimedia; Human–computer interaction; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003255515,0.0005602169,0.0005617723,0.0003264572,0.0003149407,0.0004629089,0.002503483,0.0002220542,0.00002095205],"category_scores_gemma":[0.00002186097,0.0004567499,0.0001562548,0.0001845868,0.0005447535,0.0008287272,0.0007527922,0.0006572818,0.0001492777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001201631,"about_ca_system_score_gemma":0.00008386547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002209137,"about_ca_topic_score_gemma":0.0003890516,"domain_scores_codex":[0.9970909,0.0000621279,0.0007244174,0.001015586,0.0005121348,0.0005948784],"domain_scores_gemma":[0.9964777,0.001918327,0.0003060618,0.001088506,0.00006344024,0.0001460076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008205768,0.00000736802,0.00003764472,0.00001234419,0.00001848624,0.00003862191,0.0006760933,0.00312425,3.322448e-7,0.3612975,0.000870257,0.6339089],"study_design_scores_gemma":[0.000100391,0.00009455316,0.00006903739,0.0003449486,0.00000765938,0.00005057701,0.00001845056,0.03961372,0.00001826236,0.1986508,0.760456,0.0005756307],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0001590367,0.04029923,0.5734339,0.00351057,0.008813155,0.001115429,0.00001367972,0.0006205999,0.3720344],"genre_scores_gemma":[0.06806398,0.3432742,0.332802,0.01098161,0.004134331,0.0002574092,0.00006483487,0.000706079,0.2397155],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7595857,"threshold_uncertainty_score":0.9997884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01366072652057465,"score_gpt":0.2638103586101838,"score_spread":0.2501496320896092,"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."}}