{"id":"W4287552350","doi":"10.48550/arxiv.2012.08265","title":"Signaling Games for Log-Concave Distributions: Number of Bins and\\n Properties of Equilibria","year":2020,"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":"Queen's University","funders":"","keywords":"Mathematics; Gaussian; Countable set; Context (archaeology); Upper and lower bounds; Convergence (economics); Applied mathematics; Discrete mathematics; Mathematical analysis","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":[],"consensus_categories":[],"category_scores_codex":[0.0006280793,0.0001677241,0.0004579489,0.0001040481,0.00009089687,0.00004097384,0.0007818593,0.0001506391,0.0001015954],"category_scores_gemma":[0.0007799866,0.000149285,0.0002332942,0.0004772219,0.0004858247,0.0001396557,0.0007424783,0.0001700552,0.00002652872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002790637,"about_ca_system_score_gemma":0.0001456743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002774248,"about_ca_topic_score_gemma":0.000005541222,"domain_scores_codex":[0.9985052,0.0001386227,0.0004387589,0.0006319669,0.000129568,0.0001558794],"domain_scores_gemma":[0.9976952,0.0006423187,0.0005345343,0.0005829461,0.00044714,0.00009785949],"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":[0.0003685382,0.0001638983,0.008416194,0.0002771322,0.0001841098,0.000005000729,0.0009779994,0.008287076,0.04094075,0.9392707,0.0003772895,0.0007313078],"study_design_scores_gemma":[0.0005245678,0.00006239868,0.0008231922,0.0001818356,0.0001993689,0.000001900832,0.002016095,0.02938031,0.04108286,0.9245468,0.0008837474,0.0002969083],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8882719,0.00006727309,0.1099875,0.0001852421,0.00006483102,0.0004057593,0.0003918182,0.00002845358,0.0005972052],"genre_scores_gemma":[0.9987689,0.00003415351,0.0004807594,0.00001661884,0.00003104551,0.000003946737,0.00001964694,0.000009197582,0.0006357899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1104969,"threshold_uncertainty_score":0.6087667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2986719326376997,"score_gpt":0.2900127444635379,"score_spread":0.00865918817416178,"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."}}