{"id":"W2783444524","doi":"10.3386/w24839","title":"Artificial Intelligence, Economics, and Industrial Organization","year":2018,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":192,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Artificial intelligence; Data science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003954867,0.0002414115,0.0004240939,0.001432881,0.0002340416,0.0004861079,0.0006301984,0.0005562028,0.002757811],"category_scores_gemma":[0.00297863,0.000252153,0.00006259733,0.0005439214,0.0005632512,0.0009351015,0.0006098591,0.0005048176,0.00109896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005113056,"about_ca_system_score_gemma":0.001872779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002644884,"about_ca_topic_score_gemma":0.0005133665,"domain_scores_codex":[0.9973677,0.00002340598,0.0008934634,0.0006257916,0.0007474372,0.000342199],"domain_scores_gemma":[0.994794,0.0002642135,0.0005677547,0.0002967562,0.004052978,0.0000243602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005597804,0.00008856255,0.002653777,0.000229215,0.0001087008,0.000001218837,0.00001212209,0.000105067,0.00001684542,0.7774172,0.1866487,0.03266263],"study_design_scores_gemma":[0.00008616542,0.00002871222,0.000369604,0.0001637997,0.00004087497,0.00001124036,0.00007383136,0.001826794,0.000623035,0.5627312,0.4336005,0.0004442979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03156436,0.0004453565,0.0001881912,0.003590311,0.007228453,0.001504607,0.0002991351,0.00009490032,0.9550847],"genre_scores_gemma":[0.9588783,0.002750984,0.0001181231,0.0001056932,0.03123098,0.00003708206,0.003516311,0.0001207854,0.003241788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9518429,"threshold_uncertainty_score":0.9999931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5954329123919153,"score_gpt":0.4879125325149625,"score_spread":0.1075203798769528,"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."}}