{"id":"W4401199595","doi":"10.2139/ssrn.4911237","title":"Monotone Equilibrium Design for Matching Markets with Signaling","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; McMaster University","funders":"","keywords":"Matching (statistics); Monotone polygon; Mathematical economics; Economics; Mathematics; Computer science; Microeconomics; Mathematical optimization; Statistics; Geometry","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.003864381,0.000361207,0.0007309488,0.0005864211,0.0001583223,0.0003916409,0.0004853845,0.0002054065,0.0003161448],"category_scores_gemma":[0.00003457841,0.0003604043,0.0005370513,0.0002252383,0.00002862948,0.0001012148,0.0002007402,0.003040047,0.0001731058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009535389,"about_ca_system_score_gemma":0.001112552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006558401,"about_ca_topic_score_gemma":0.00005073802,"domain_scores_codex":[0.9965422,0.00005339469,0.0008776864,0.0006514249,0.00009184414,0.001783469],"domain_scores_gemma":[0.9987515,0.00007884449,0.0006314103,0.0003421227,0.00007818321,0.0001179107],"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":[0.0003287509,0.00009575085,0.0002761493,0.0002642837,0.0031758,0.00001440485,0.0003629034,0.02379123,0.0001318087,0.9695313,0.0005043226,0.001523285],"study_design_scores_gemma":[0.0003981072,0.000141438,0.00001837766,0.0001485425,0.0001517518,0.00009017319,0.0002832708,0.01238954,0.00009138969,0.984295,0.001527493,0.000464937],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05938907,0.02729638,0.9067692,0.001440469,0.0008709268,0.0004555231,0.0000770312,0.00008372538,0.003617699],"genre_scores_gemma":[0.9851359,0.003321974,0.003717867,0.000124954,0.0007257012,0.0001080059,0.00003784215,0.0001197099,0.006708096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9257468,"threshold_uncertainty_score":0.9998848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02429686018412673,"score_gpt":0.2338055398131371,"score_spread":0.2095086796290104,"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."}}