{"id":"W3183186537","doi":"10.3982/te3665","title":"Revenue from matching platforms","year":2021,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"National Science Foundation","keywords":"Economics; Microeconomics; Matching (statistics); Revenue; Homogeneity (statistics); Contrast (vision); Econometrics; Revenue management; Computer science; Mathematics; Statistics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008818928,0.0000766586,0.0001758815,0.00002907919,0.0001434115,0.0001564433,0.000372055,0.00006835885,0.008357103],"category_scores_gemma":[0.0006345926,0.00006291388,0.0000926012,0.0001289825,0.0002974129,0.0001590903,0.0001386714,0.0001321567,0.003380989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002496192,"about_ca_system_score_gemma":0.00005282127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003801415,"about_ca_topic_score_gemma":0.000008176911,"domain_scores_codex":[0.9989837,0.00004872498,0.0003860928,0.0003329383,0.0001073598,0.0001411496],"domain_scores_gemma":[0.9978667,0.001283471,0.0000938732,0.0005892522,0.00005742997,0.0001092079],"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":[0.00001082425,0.0000168744,0.00006464763,2.203623e-7,0.000005952947,0.000001604193,0.0001786116,0.0001628781,0.0001458956,0.9906941,0.0004248829,0.008293523],"study_design_scores_gemma":[0.0001003631,0.000004303854,0.0003670625,0.000002580254,0.000005556256,0.000008265999,0.0005474898,0.0007175166,0.003046344,0.9802223,0.01489357,0.00008462972],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.931077,0.00002609271,0.03645972,0.002106555,0.0002525343,0.00004096479,0.0001124107,0.00002573029,0.02989898],"genre_scores_gemma":[0.994693,0.00002697371,0.002641981,0.0009369264,0.0002056848,0.000006313522,0.00001654414,0.000009211383,0.0014633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06361605,"threshold_uncertainty_score":0.997395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05417026244484652,"score_gpt":0.3382103280852857,"score_spread":0.2840400656404392,"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."}}