{"id":"W2418437014","doi":"10.2139/ssrn.2798611","title":"Search Frictions, Competing Mechanisms and Optimal Market Segmentation","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Market segmentation; Segmentation; Economics; Computer science; Microeconomics; Business; Econometrics; 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":[0.006714776,0.000692954,0.002826111,0.001594153,0.001499974,0.005485033,0.002214292,0.00496643,0.01159846],"category_scores_gemma":[0.03576346,0.001154602,0.001013791,0.001600843,0.00399043,0.007933309,0.002471738,0.002086353,0.0006485902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001929032,"about_ca_system_score_gemma":0.002354804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001093741,"about_ca_topic_score_gemma":0.001069153,"domain_scores_codex":[0.9976821,0.001137368,0.0001372629,0.0002714718,0.0002479445,0.0005238464],"domain_scores_gemma":[0.9771287,0.01567469,0.004191938,0.001203479,0.0004682172,0.001332869],"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":[0.0008874566,0.0003216508,0.003050396,0.0003113485,0.0001372563,0.0003678051,0.0003560272,0.09327424,0.001228154,0.8800234,0.002466332,0.01757595],"study_design_scores_gemma":[0.0002635194,0.0001322919,0.001702566,0.00005326263,0.00004305662,0.0001401722,0.0002407481,0.128074,0.0002111977,0.8682362,0.0008631641,0.00003981057],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7442726,0.003325106,0.2066801,0.004856018,0.0001940424,0.0001859626,0.0001782632,0.0001941372,0.04011383],"genre_scores_gemma":[0.9867576,0.0003570075,0.008472164,0.0001153755,0.0000467658,0.0000545852,0.00002987587,0.00001682068,0.004149804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01159846,"threshold_uncertainty_score":0.03880072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011446350592299,"score_gpt":0.3380372393895489,"score_spread":0.3079227758836259,"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."}}