{"id":"W2544689273","doi":"","title":"AI Algorithms and Stochastic Game‐play","year":2015,"lang":"en","type":"article","venue":"URSCA Proceedings","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Computer science; Algorithm; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003042375,0.0007585056,0.0009810616,0.0009477621,0.001343609,0.004715844,0.001432445,0.001855841,0.00794447],"category_scores_gemma":[0.01577279,0.0004764225,0.0009441799,0.001337533,0.005033638,0.004957593,0.002329953,0.003477566,0.0005810889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003033852,"about_ca_system_score_gemma":0.001777037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003468427,"about_ca_topic_score_gemma":0.002737457,"domain_scores_codex":[0.9974775,0.001423827,0.0001115308,0.0003114307,0.000466329,0.0002093291],"domain_scores_gemma":[0.9892082,0.008942726,0.0004500398,0.0005139885,0.000465467,0.0004196283],"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":[0.00001480411,0.0000178989,0.0001550591,0.00002352888,0.00001224382,0.00001036739,0.00007517337,0.008849938,0.00006868938,0.9846897,0.0009502543,0.005132488],"study_design_scores_gemma":[0.000006182399,0.000004829854,0.00006365436,0.000006470633,0.000003557296,0.000008980397,0.00002010349,0.03829302,0.00003694065,0.9598726,0.001679733,0.000003963031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05952572,0.004157265,0.823827,0.01388616,0.0006214922,0.00008011822,0.0001608362,0.0002705182,0.09747081],"genre_scores_gemma":[0.9015791,0.002070236,0.06688794,0.001026549,0.0007041463,0.0002178894,0.0001971415,0.00009818967,0.02721888],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00794447,"threshold_uncertainty_score":0.02657688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0262662365523519,"score_gpt":0.2599431845631732,"score_spread":0.2336769480108213,"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."}}