{"id":"W2382996178","doi":"10.1142/s0219198916400028","title":"Strategic Support of Node-Consistent Cooperative Outcomes in Dynamic Games Played Over Event Trees","year":2016,"lang":"en","type":"article","venue":"International Game Theory Review","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Subgame perfect equilibrium; Event (particle physics); Node (physics); Sequential game; Mathematical economics; Game tree; Subgame; Computer science; Extensive-form game; Tree (set theory); Backward induction; Non-cooperative game; Microeconomics; Repeated game; Operations research; Economics; Game theory; Mathematics; Equilibrium selection; Combinatorics; Engineering; Physics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003689157,0.0002099882,0.0006297735,0.0002175668,0.00002537047,0.00004044497,0.001069896,0.00005161802,0.009047914],"category_scores_gemma":[0.001591887,0.0001137864,0.0002903633,0.0003300874,0.0002765503,0.0002506897,0.000138403,0.0001036371,0.0008029756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009116656,"about_ca_system_score_gemma":0.0001031517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004500238,"about_ca_topic_score_gemma":0.00004291542,"domain_scores_codex":[0.9965932,0.0006170836,0.001303872,0.0004521972,0.0008397296,0.0001938851],"domain_scores_gemma":[0.9959413,0.002470293,0.0005302769,0.0006083499,0.0003728553,0.00007687508],"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":[0.0001758897,0.0005249246,0.007499588,0.00006431573,0.0001980162,0.00001462042,0.0002945329,0.0000871997,0.003693667,0.9076626,0.0009366107,0.07884805],"study_design_scores_gemma":[0.001923249,0.0002012278,0.05178457,0.002780779,0.00009904841,0.00004718273,0.0004354157,0.0002102065,0.001037527,0.8849497,0.05594992,0.0005811878],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8871265,0.01116539,0.008853111,0.02159632,0.0009648005,0.002070677,0.0009397069,0.00009747609,0.06718601],"genre_scores_gemma":[0.9831356,0.00328787,0.00006949076,0.001128218,0.00001599441,0.0001085361,0.00001150703,0.00001203468,0.01223075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09600908,"threshold_uncertainty_score":0.999975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08526420958749709,"score_gpt":0.420012833805227,"score_spread":0.3347486242177299,"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."}}