{"id":"W3201202131","doi":"10.48550/arxiv.2109.03370","title":"Monotone Equilibrium in Matching Markets with Signaling","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Monotone polygon; Communication source; Matching (statistics); Sobel operator; Mathematics; Set (abstract data type); Strongly monotone; Order (exchange); Mathematical economics; Mathematical optimization; Computer science; Economics; Statistics; Artificial intelligence","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":[0.004787589,0.000910629,0.001444212,0.001103081,0.001044037,0.002947065,0.001882071,0.002778003,0.005339998],"category_scores_gemma":[0.01402702,0.0005455327,0.001416297,0.001239002,0.003627697,0.006633203,0.002169354,0.002225755,0.0005493588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00212681,"about_ca_system_score_gemma":0.001311049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008610032,"about_ca_topic_score_gemma":0.0006287813,"domain_scores_codex":[0.9949179,0.002441084,0.0002746427,0.0007740432,0.0009452988,0.000647034],"domain_scores_gemma":[0.9924735,0.004413858,0.001353598,0.0006275191,0.0006729646,0.0004585667],"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":[0.00005126561,0.00005983711,0.0002993791,0.00007269544,0.0000222598,0.00008398195,0.0001151298,0.01693429,0.001889187,0.9757068,0.0003092765,0.004455941],"study_design_scores_gemma":[0.00005917767,0.00007257802,0.0001576295,0.00001519421,0.00001058942,0.00007797877,0.00004876591,0.1299361,0.0006077269,0.8678223,0.001174058,0.00001786788],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1998592,0.0004989483,0.7656421,0.001781304,0.00008001263,0.0002949307,0.0002834136,0.0002429606,0.03131713],"genre_scores_gemma":[0.8924706,0.0003914531,0.1012725,0.0004443478,0.0001505426,0.0003424864,0.0001423278,0.0000438734,0.004741923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005339998,"threshold_uncertainty_score":0.02531952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07155029950719388,"score_gpt":0.1671499527032206,"score_spread":0.09559965319602676,"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."}}