{"id":"W3123791853","doi":"","title":"Estimating the Effect of Salience in Wholesale and Retail Car Markets","year":2013,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Odometer; Salient; Salience (neuroscience); Database transaction; Retail market; Business; Econometrics; Classification of discontinuities; Commerce; Economics; Marketing; Mathematics; Computer science","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":[0.004565229,0.0003924729,0.0008828823,0.000898589,0.000455657,0.002252673,0.0009272339,0.001424318,0.003873278],"category_scores_gemma":[0.04552354,0.0004709429,0.0007754439,0.001091424,0.001035612,0.002544059,0.001391483,0.001864326,0.0003538707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007228157,"about_ca_system_score_gemma":0.0004905522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01134773,"about_ca_topic_score_gemma":0.006337489,"domain_scores_codex":[0.9983108,0.0008580174,0.00008808741,0.0003535442,0.0001762305,0.0002133227],"domain_scores_gemma":[0.9280265,0.06177766,0.006139609,0.002176802,0.0008050236,0.001074317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002214777,0.001466476,0.9253249,0.0001540045,0.0003074229,0.0003405286,0.0009081399,0.02939071,0.004519862,0.008031836,0.0007933729,0.026548],"study_design_scores_gemma":[0.0002776021,0.00105827,0.7460551,0.0000254998,0.0002793723,0.0001305903,0.001536943,0.2343319,0.003390155,0.01184654,0.000993442,0.00007458984],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975663,0.00005960143,0.001690646,0.00008083916,0.000003883026,0.00001384188,0.00008270114,0.000009863425,0.0004922667],"genre_scores_gemma":[0.9988545,0.00001972353,0.0008224473,0.00001519745,0.000006894066,0.000006342299,0.0001395525,0.000003103238,0.0001321582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01134773,"threshold_uncertainty_score":0.02414352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02302189272044892,"score_gpt":0.2826593845457539,"score_spread":0.259637491825305,"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."}}