{"id":"W1516840567","doi":"10.1007/978-0-387-35706-5_23","title":"Solving the Oshi-Zumo Game","year":2004,"lang":"en","type":"book-chapter","venue":"Advances in Computer Games","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Nash equilibrium; Mathematical economics; Computer science; Game theory; Strategy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005267833,0.0008497876,0.0008591171,0.0002998178,0.0009768691,0.001423722,0.001042575,0.001200693,0.009859203],"category_scores_gemma":[0.001763861,0.0002604438,0.0006375447,0.0004321684,0.0009702746,0.002728687,0.001573125,0.001597257,0.0006703345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006020729,"about_ca_system_score_gemma":0.001216025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002030113,"about_ca_topic_score_gemma":0.004391118,"domain_scores_codex":[0.9997533,0.00008836414,0.00001341924,0.00003710962,0.00005039497,0.00005740064],"domain_scores_gemma":[0.9997037,0.0002026732,0.00001616731,0.00002456914,0.0000177506,0.00003507362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002369277,0.0001254593,0.0004117235,0.0002184794,0.00004391059,0.0001266634,0.0005939268,0.04736306,0.002808198,0.8737898,0.006573274,0.06770874],"study_design_scores_gemma":[0.00008991526,0.0001093637,0.0002544609,0.00006525243,0.00003678271,0.00006605153,0.0004800223,0.1993517,0.002081406,0.7783293,0.01910674,0.00002906643],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1526174,0.0007288242,0.6028398,0.00213795,0.0004466914,0.0002968461,0.0001802323,0.000284825,0.2404674],"genre_scores_gemma":[0.6781561,0.001279379,0.2167871,0.0003663268,0.0001181445,0.0004378598,0.0002934972,0.0001120522,0.1024496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009859203,"threshold_uncertainty_score":0.03298235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05315334453245216,"score_gpt":0.3524715400949214,"score_spread":0.2993181955624692,"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."}}