{"id":"W4408141514","doi":"10.1093/restud/rdaf014","title":"Simultaneous Search and Adverse Selection","year":2025,"lang":"en","type":"article","venue":"The Review of Economic Studies","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Deutsche Forschungsgemeinschaft","keywords":"Adverse selection; Economics; Selection (genetic algorithm); Econometrics; Microeconomics; Computer science; Machine learning","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":[0.00463637,0.0007496411,0.002253966,0.001226266,0.00110157,0.002952415,0.001721876,0.002858511,0.008915622],"category_scores_gemma":[0.02297154,0.0005889,0.00155061,0.0009303565,0.0043243,0.004682383,0.003367955,0.002260072,0.0006879629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093629,"about_ca_system_score_gemma":0.0007499694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001367746,"about_ca_topic_score_gemma":0.000796402,"domain_scores_codex":[0.9962031,0.002151096,0.0001411527,0.0004279935,0.0004312933,0.0006452382],"domain_scores_gemma":[0.9753011,0.01698963,0.00410024,0.001608902,0.0007190026,0.001281199],"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":[0.0004407341,0.0002495781,0.00669644,0.0003771598,0.0003264177,0.001765912,0.0006555215,0.2461469,0.003681653,0.713169,0.003695007,0.02279573],"study_design_scores_gemma":[0.0002358345,0.0002393746,0.001846392,0.00005751441,0.0000655905,0.0004470831,0.0001963695,0.394908,0.0005367658,0.5992807,0.002122252,0.00006418914],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5896062,0.002189163,0.3624263,0.004591211,0.0001984754,0.0001845525,0.0002194665,0.0002318354,0.04035277],"genre_scores_gemma":[0.992186,0.0003224144,0.003701506,0.0001709615,0.00007792124,0.00005511391,0.00002260598,0.000009125023,0.003454372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008915622,"threshold_uncertainty_score":0.02982575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01904117740346099,"score_gpt":0.3323290739836644,"score_spread":0.3132878965802034,"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."}}