{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007633935,0.00008550575,0.0001067791,0.0001732203,0.0006769216,0.0001503787,0.0002688866,0.00004148698,0.0007416497],"category_scores_gemma":[0.0002714358,0.00005221854,0.00005509986,0.0002919782,0.00007093544,0.0004015286,0.00005565428,0.0004325497,0.0001697037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002364172,"about_ca_system_score_gemma":0.0003463043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003677119,"about_ca_topic_score_gemma":0.00001629493,"domain_scores_codex":[0.9977798,0.000305576,0.0003440664,0.0002388164,0.0005382476,0.0007934707],"domain_scores_gemma":[0.9988666,0.000552502,0.0001633376,0.0001646737,0.0001597081,0.00009324103],"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":[0.00004351641,0.0000268206,0.0008270887,4.363751e-7,0.00003007161,5.524269e-7,0.0001545018,0.00003873612,0.01383818,0.7746297,0.0003700448,0.2100404],"study_design_scores_gemma":[0.0004693838,0.0001228264,0.0008257401,0.000008092911,0.00001164147,0.0005202074,0.01126966,0.0003636532,0.002370461,0.9814596,0.002470349,0.0001084334],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1833235,0.0001706821,0.8116866,0.003306739,0.0001021416,0.00008525133,0.000004141279,0.00002428136,0.001296619],"genre_scores_gemma":[0.9875891,0.0007116608,0.00294822,0.00005961042,0.000137958,0.000008029906,5.140484e-7,0.000008836886,0.008536056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8087384,"threshold_uncertainty_score":0.8120544,"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."}}