{"id":"W3048361030","doi":"10.3386/w27649","title":"Assessing the Quality of Illegal Copies and its Impact on Revenues and Distribution","year":2020,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Copyright and Intellectual Property","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Estimation; Revenue; Quality (philosophy); Distribution (mathematics); Econometrics; Statistics; Motion (physics); Computer science; Economics; Mathematics; Artificial intelligence; Finance","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00481936,0.0003878034,0.0004505636,0.002099785,0.0003583709,0.002442278,0.0005217345,0.0005397826,0.005270493],"category_scores_gemma":[0.04076434,0.0003046847,0.0005184959,0.001950613,0.001005311,0.002780369,0.001015148,0.0009327671,0.001029096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395284,"about_ca_system_score_gemma":0.001042932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009189421,"about_ca_topic_score_gemma":0.0113525,"domain_scores_codex":[0.9967902,0.001014156,0.0002154221,0.0004035375,0.001391028,0.0001856537],"domain_scores_gemma":[0.9335155,0.03994799,0.01727158,0.003741934,0.004391954,0.00113104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002092705,0.0002313682,0.9664043,0.00007667199,0.0001458601,0.00009617794,0.0002570303,0.005659744,0.00085937,0.002206516,0.000517629,0.02333602],"study_design_scores_gemma":[0.00001531867,0.0004136376,0.9570094,0.00003713724,0.0001030105,0.0001469014,0.000865899,0.03428923,0.00297521,0.002655978,0.001449041,0.00003941979],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825471,0.0002360679,0.005892159,0.0002737592,0.000009438573,0.00009142497,0.001237963,0.00004888239,0.009663173],"genre_scores_gemma":[0.9948468,0.0001153305,0.002593768,0.0000188758,0.000007569682,0.00001625482,0.0009083523,0.00001141371,0.001481569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009189421,"threshold_uncertainty_score":0.02548754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4716021322664249,"score_gpt":0.5430494252995566,"score_spread":0.07144729303313163,"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."}}