{"id":"W2119621836","doi":"10.2139/ssrn.2133302","title":"The Logic of Backward Induction","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","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":[0.006468912,0.001105498,0.001521093,0.002179692,0.003637585,0.005451229,0.002622052,0.002444655,0.01393852],"category_scores_gemma":[0.01167367,0.001565035,0.002967725,0.002614178,0.01016602,0.01470826,0.00556848,0.009375622,0.003850739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004706735,"about_ca_system_score_gemma":0.002788786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003986391,"about_ca_topic_score_gemma":0.002752823,"domain_scores_codex":[0.995562,0.002011969,0.0002852581,0.0009084204,0.0008075545,0.0004248036],"domain_scores_gemma":[0.9920657,0.005475045,0.000269395,0.000998249,0.0009679745,0.0002236576],"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":[0.00001114246,0.000006641351,0.00003582749,0.00002377754,0.000007279809,0.00001109874,0.00006795239,0.0002263866,0.00009126621,0.9954,0.001486637,0.002631983],"study_design_scores_gemma":[0.000007910839,0.000002146663,0.00001667521,0.000008845721,0.000004830701,0.000008622585,0.000008194384,0.0006882452,0.0001046225,0.9962397,0.002906622,0.000003629698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01123228,0.002945793,0.7141253,0.01423867,0.0007120289,0.0001296198,0.001064816,0.0005964137,0.2549551],"genre_scores_gemma":[0.5633476,0.004869878,0.3130394,0.008460982,0.001664712,0.0009902517,0.002091959,0.0008700879,0.1046651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01393852,"threshold_uncertainty_score":0.04662901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07901242858771615,"score_gpt":0.3779603423382767,"score_spread":0.2989479137505605,"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."}}