{"id":"W2973606980","doi":"10.48550/arxiv.1909.09320","title":"Discerning Solution Concepts","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Counterfactual thinking; Nash equilibrium; Identification (biology); Mathematical economics; Set (abstract data type); Solution concept; Stochastic game; Covariate; Computer science; Risk dominance; Best response; Epsilon-equilibrium; Econometrics; Mathematics; Social psychology; Psychology","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":[0.02201142,0.00202811,0.00228865,0.006745814,0.00221708,0.00749934,0.002327599,0.004252856,0.008230437],"category_scores_gemma":[0.09023923,0.0013116,0.002881414,0.003112291,0.00913796,0.01623883,0.007472251,0.006476617,0.0007742749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002918591,"about_ca_system_score_gemma":0.003926968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001210883,"about_ca_topic_score_gemma":0.0007077371,"domain_scores_codex":[0.9865139,0.005357979,0.001359141,0.003784903,0.002023484,0.0009606804],"domain_scores_gemma":[0.9235219,0.05865315,0.00821492,0.004280911,0.0033783,0.001950893],"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":[0.00004710152,0.0000688023,0.0009137261,0.0001328831,0.00003184131,0.00005764925,0.0004393085,0.01255775,0.0002808413,0.9730546,0.0006617274,0.0117538],"study_design_scores_gemma":[0.00002553253,0.00003081818,0.0001729991,0.00007267004,0.000009497417,0.00003134382,0.0001783906,0.04104727,0.0002623535,0.9571146,0.001034899,0.00001950428],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08875172,0.0008168051,0.8837449,0.003454334,0.0001279817,0.000381088,0.0008335619,0.0001835113,0.02170625],"genre_scores_gemma":[0.6057852,0.0009312421,0.3880716,0.000590198,0.0002024055,0.000842236,0.001201491,0.0001219888,0.00225361],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02201142,"threshold_uncertainty_score":0.1164089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2712411035894527,"score_gpt":0.2991762161213254,"score_spread":0.02793511253187275,"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."}}