{"id":"W2145893117","doi":"10.1080/13501780050045092","title":"Data mining and the econometrics industry: comments on the papers of Mayer and of Hoover and Perez","year":2000,"lang":"en","type":"article","venue":"Journal of Economic Methodology","topic":"Data Analysis with R","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Analogy; Incentive; Competition (biology); Product (mathematics); Economics; Quality (philosophy); Sensitivity (control systems); Process (computing); Econometrics; Econometric model; Econometric analysis; Computer science; Microeconomics; Engineering; Mathematics; Epistemology","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":[0.006289449,0.00008227576,0.0004500819,0.0001665656,0.00004417762,0.00004293138,0.0008985145,0.00007424732,0.0001584908],"category_scores_gemma":[0.0005351229,0.00004626373,0.00003485236,0.00009257667,0.0002835223,0.0002844485,0.0003672333,0.0002138817,7.610136e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001417056,"about_ca_system_score_gemma":0.00004269434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003148885,"about_ca_topic_score_gemma":0.00001478443,"domain_scores_codex":[0.998347,0.0008020751,0.0005143353,0.000178194,0.00005574082,0.0001025902],"domain_scores_gemma":[0.9937918,0.004936516,0.0006449196,0.0005569219,0.00001829912,0.00005151055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007304538,0.0001151366,0.1036517,0.00005300928,0.002154328,0.00001388745,0.004309049,0.0006888728,0.0002974597,0.04692498,0.0187986,0.8222626],"study_design_scores_gemma":[0.02489911,0.003346243,0.555092,0.0003502817,0.001978103,0.003041134,0.008863348,0.2004278,0.001996411,0.0462816,0.1522682,0.001455703],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990862,0.0005238096,0.001429808,0.005636092,0.0001146992,0.00005991358,0.00003356292,9.908035e-7,0.001339134],"genre_scores_gemma":[0.9158808,0.001575492,0.08032976,0.001962871,0.00008243817,8.64975e-7,0.00000175227,0.000007784348,0.0001582096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8208069,"threshold_uncertainty_score":0.217981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3150617068011859,"score_gpt":0.3634951639902002,"score_spread":0.04843345718901421,"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."}}