{"id":"W2974598553","doi":"10.3386/w26296","title":"Too Much Data: Prices and Inefficiencies in Data Markets","year":2019,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":205,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Economics; Econometrics; Monetary economics; Business","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":[0.008285386,0.0001941488,0.0004584623,0.001174027,0.00007329864,0.0009697031,0.001970885,0.0002102955,0.0002053041],"category_scores_gemma":[0.001726938,0.0001884159,0.00003217917,0.0002154584,0.0001781609,0.007414415,0.004016062,0.000408849,0.0003092794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003419904,"about_ca_system_score_gemma":0.001330192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003187272,"about_ca_topic_score_gemma":0.001741761,"domain_scores_codex":[0.9973608,0.000003574675,0.0006887569,0.0008353624,0.0007390856,0.0003724062],"domain_scores_gemma":[0.9975533,0.0005056878,0.0004090672,0.0009888523,0.0005256416,0.00001737696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001364868,0.0002221638,0.01526309,0.00214068,0.0001871258,0.000009327133,0.00001744196,0.0002966891,0.000008630534,0.3453292,0.6204934,0.01589579],"study_design_scores_gemma":[0.0007383092,0.00001537077,0.01255655,0.0002434049,0.00001974678,0.00001060389,0.0003950172,0.04010923,0.000001889958,0.1467171,0.7986636,0.0005292371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1305777,0.0005850733,8.223891e-7,0.0003878496,0.0005071071,0.0004604816,0.0003300818,0.00001160439,0.8671393],"genre_scores_gemma":[0.9708418,0.001646299,0.0001083804,0.0001331631,0.002407227,0.00002045881,0.01476025,0.00006311736,0.01001925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8571201,"threshold_uncertainty_score":0.935087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.581126406768884,"score_gpt":0.4935151753971544,"score_spread":0.0876112313717296,"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."}}