{"id":"W4365807313","doi":"10.2139/ssrn.4404772","title":"Machine Learning for Economics Research: When What and How?","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Economics education; Economics; Computer science; Artificial intelligence; Mathematics education; Data science; Machine learning; Psychology","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":[0.03292064,0.0008782604,0.002980776,0.003531049,0.001568224,0.01350504,0.001809434,0.005683661,0.01010222],"category_scores_gemma":[0.1110033,0.0007242437,0.0009556103,0.004111839,0.008143371,0.0254261,0.002380228,0.01011411,0.003557159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003473608,"about_ca_system_score_gemma":0.006163557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005022558,"about_ca_topic_score_gemma":0.008189873,"domain_scores_codex":[0.9856791,0.01049391,0.0005391759,0.0006497721,0.002218604,0.0004194038],"domain_scores_gemma":[0.8699397,0.1090979,0.002766979,0.004054988,0.01072308,0.003417405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001729576,0.0002680731,0.005452144,0.002269923,0.0002724794,0.00005247275,0.0005535758,0.002079339,0.0002204111,0.1337297,0.1436334,0.7112955],"study_design_scores_gemma":[0.0001101811,0.0001349912,0.003451275,0.007136245,0.000181803,0.00009171345,0.001991753,0.02199191,0.0006455208,0.7939979,0.170106,0.0001607619],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.004953155,0.2511568,0.06549433,0.6545419,0.008451429,0.0001496787,0.000524536,0.000362112,0.01436607],"genre_scores_gemma":[0.2472059,0.4158888,0.1713593,0.1017048,0.04303932,0.001161542,0.0006273101,0.0007604317,0.01825247],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03292064,"threshold_uncertainty_score":0.1741031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2458095346805196,"score_gpt":0.4436653148556958,"score_spread":0.1978557801751762,"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."}}