{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001200311,0.000272988,0.0002892505,0.001626039,0.0009734306,0.004349498,0.000250072,0.001000596,0.01291253],"category_scores_gemma":[0.003866452,0.0001331497,0.0001342685,0.005964683,0.001809571,0.00262164,0.0009001478,0.00179244,0.001340505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003237206,"about_ca_system_score_gemma":0.002966787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007086437,"about_ca_topic_score_gemma":0.009380309,"domain_scores_codex":[0.9991161,0.0002612121,0.00004599553,0.0000833399,0.0003348242,0.0001585479],"domain_scores_gemma":[0.9979296,0.0009440581,0.0004614181,0.000109495,0.0003253105,0.0002300107],"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":[0.00002248739,0.00006863138,0.01710268,0.0002257131,0.0000292706,0.00007923802,0.0005164205,0.001170442,0.0000549138,0.7996933,0.07902694,0.10201],"study_design_scores_gemma":[0.00001086895,0.00004704957,0.06691689,0.0007193745,0.00001364103,0.0001239253,0.002310728,0.0008303308,0.0001016504,0.446744,0.482156,0.00002559627],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04227589,0.1495231,0.003950434,0.1063422,0.001237801,0.0001071799,0.001397477,0.00009658653,0.6950694],"genre_scores_gemma":[0.6555968,0.2510045,0.003655281,0.007507591,0.002982215,0.0002001142,0.001633025,0.00004536113,0.07737515],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01291253,"threshold_uncertainty_score":0.04319674,"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."}}