{"id":"W4376457117","doi":"10.2139/ssrn.4444283","title":"Search Frictions, Sorting, and Matching in Two-Sided Markets","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Sorting; Matching (statistics); Economics; Mathematics; Econometrics; Computer science; Statistics; Algorithm","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":[0.007771037,0.00009853279,0.0002255949,0.0004411206,0.0002100328,0.00008963964,0.0001439484,0.00004353244,0.00003946731],"category_scores_gemma":[0.0001457161,0.0001103685,0.00005687616,0.0003839992,0.00002116106,0.0001722834,0.00004403367,0.001119929,0.0002758471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003176987,"about_ca_system_score_gemma":0.0001253129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003408552,"about_ca_topic_score_gemma":0.000420697,"domain_scores_codex":[0.9977947,0.00007922183,0.0004964676,0.0002121378,0.00004094655,0.001376533],"domain_scores_gemma":[0.9995232,0.0001100044,0.0001864075,0.000112415,0.00001242355,0.00005558159],"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":[0.00001732481,0.00001628306,0.1192388,0.00001012906,0.00004093519,0.000006412316,0.000744032,0.0002053152,0.00005369268,0.8774399,0.00003373094,0.002193506],"study_design_scores_gemma":[0.0006577931,0.00004238826,0.02805527,0.00003956322,0.000002404554,0.0001974432,0.002672989,0.001442527,0.00001294904,0.9663518,0.0003748445,0.0001500024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905293,0.002088786,0.001203331,0.0004616219,0.0002329239,0.00008170142,0.000002868077,0.00004484949,0.005354639],"genre_scores_gemma":[0.9950274,0.001749997,0.0000254275,0.00002840995,0.0001633101,0.000004635949,0.000002051785,0.00002092872,0.002977793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0911835,"threshold_uncertainty_score":0.4865598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02178946708811659,"score_gpt":0.2614106593583039,"score_spread":0.2396211922701873,"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."}}