{"id":"W3122744194","doi":"10.1257/mic.3.4.1","title":"Platform Siphoning: Ad-Avoidance and Media Content","year":2011,"lang":"en","type":"article","venue":"American Economic Journal Microeconomics","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Profitability index; Content (measure theory); Advertising; Business; Quality (philosophy); Mathematics; Physics","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":[0.001381426,0.0003094595,0.0001822362,0.0007471214,0.0009001799,0.00469988,0.000467137,0.00181937,0.0201958],"category_scores_gemma":[0.009576743,0.0001797023,0.0002944264,0.0008584011,0.001886062,0.002927383,0.001182846,0.001296585,0.001226237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001785071,"about_ca_system_score_gemma":0.0006559342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002681243,"about_ca_topic_score_gemma":0.002866877,"domain_scores_codex":[0.9992571,0.0002414571,0.00003255753,0.00008353453,0.0002552911,0.0001300982],"domain_scores_gemma":[0.9902279,0.005495054,0.002575133,0.0004332993,0.0006604368,0.0006081363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001529941,0.0007896727,0.1458154,0.0007692659,0.0001277526,0.001937922,0.004565069,0.01039485,0.02148654,0.5296447,0.01925184,0.263687],"study_design_scores_gemma":[0.0002923327,0.001553072,0.3709806,0.0005518325,0.000569424,0.003453627,0.02181545,0.07647654,0.01789503,0.3414885,0.1646192,0.0003044447],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6081613,0.00166658,0.01603051,0.007062818,0.0002175358,0.0002127543,0.0002449881,0.0001622885,0.3662412],"genre_scores_gemma":[0.987399,0.0003520123,0.001053191,0.0003032601,0.0001010022,0.00001508537,0.00002637862,0.00001620117,0.0107338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0201958,"threshold_uncertainty_score":0.06756175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04787596547123225,"score_gpt":0.1888222188390411,"score_spread":0.1409462533678088,"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."}}