{"id":"W1936423809","doi":"10.1287/mksc.2015.0944","title":"Matching Value and Market Design in Online Advertising Networks: An Empirical Analysis","year":2015,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Hong Kong University of Science and Technology; Chinese University of Hong Kong; University of Hong Kong","keywords":"Counterfactual thinking; Matching (statistics); Profit (economics); Online advertising; Microeconomics; Incentive; Revenue; Advertising; Two-sided market; Mechanism design; Value (mathematics); Incentive compatibility; Economics; Network effect; Computer science; Business; The Internet","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":[0.01395836,0.0001950973,0.0002897698,0.001030938,0.0003381129,0.0008366832,0.0004619041,0.00005608247,0.0000583043],"category_scores_gemma":[0.0008927442,0.0001934416,0.00004917091,0.004338712,0.0002267288,0.0020505,0.0004240054,0.0002279135,0.000002943181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008456763,"about_ca_system_score_gemma":0.00008359383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001317221,"about_ca_topic_score_gemma":0.000572531,"domain_scores_codex":[0.9976811,0.000203258,0.0003743928,0.000644021,0.0005285528,0.0005686551],"domain_scores_gemma":[0.9988966,0.0004046308,0.0001572145,0.0003170981,0.0001473913,0.00007709156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000143602,0.00006691029,0.9385179,0.00001963218,0.00001075633,0.00002617676,0.0002211732,0.01002625,0.0001272068,0.0000373392,0.00009994605,0.05070309],"study_design_scores_gemma":[0.0001920804,0.000004178277,0.5699995,0.0000457796,0.00009255999,0.000003042587,0.000594275,0.4285062,0.000001152532,0.0002607904,0.0001205273,0.0001799397],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816524,0.0001392304,0.01392859,0.0002131685,0.0002010696,0.0001556524,5.381713e-7,0.0001054183,0.00360391],"genre_scores_gemma":[0.9919167,0.000007594108,0.007204594,0.0006039301,0.0001864907,0.000004718114,0.000004837819,0.00001679074,0.00005430481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4184799,"threshold_uncertainty_score":0.8068156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04097693701520671,"score_gpt":0.3046892982724157,"score_spread":0.263712361257209,"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."}}