{"id":"W2149631225","doi":"10.1287/opre.2016.1569","title":"Revenue-maximizing rankings for online platforms with quality-sensitive consumers","year":2015,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fondo para la Investigación Científica y Tecnológica; Consejo Nacional de Investigaciones Científicas y Técnicas","keywords":"Revenue; Quality (philosophy); Marketing; Business; Economics; Computer science; Environmental economics; Advertising; Finance","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0160078,0.0001789241,0.0003065362,0.0001704455,0.0004971402,0.0002736094,0.0007874006,0.00009355322,0.0000421256],"category_scores_gemma":[0.009261324,0.0001427039,0.0001239493,0.000808317,0.0004055968,0.000365327,0.0001685473,0.0001997479,0.00009344515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006705851,"about_ca_system_score_gemma":0.0002143258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002087071,"about_ca_topic_score_gemma":0.001149127,"domain_scores_codex":[0.9961738,0.001590185,0.000625346,0.0005836773,0.0007464908,0.0002804865],"domain_scores_gemma":[0.9879439,0.005588795,0.0006227817,0.001282094,0.004311746,0.0002507212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000273678,0.0007327176,0.002842268,0.00001871559,0.00008029899,0.000002956775,0.01857208,0.0001382943,0.002221998,0.846411,0.006261425,0.1224446],"study_design_scores_gemma":[0.006601338,0.000006122285,0.007279973,0.0006673498,0.0001080748,0.00009629966,0.01334211,0.009740266,0.08581521,0.4305277,0.4446464,0.001169193],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3594165,0.0001037429,0.6195746,0.0106786,0.000100265,0.0004862463,0.0002055746,0.0001187542,0.009315697],"genre_scores_gemma":[0.8980532,0.00002023702,0.08681762,0.0003274272,0.00002484768,0.0000649094,0.0001670042,0.00002581025,0.01449894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5386367,"threshold_uncertainty_score":0.9990841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09164388555289375,"score_gpt":0.3405725339512368,"score_spread":0.2489286483983431,"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."}}