{"id":"W4392643978","doi":"10.2139/ssrn.4754776","title":"A Practical Guide to Endogeneity Correction Using Copulas","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Endogeneity; Econometrics; Computer science; Economics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001866036,0.000159835,0.0001464048,0.0003614579,0.0003001348,0.0006841812,0.0001320763,0.00005678125,0.0002084781],"category_scores_gemma":[0.0002356934,0.0001474278,0.0001225492,0.0006042891,0.00001546852,0.0009469637,0.00009174518,0.001215582,0.0002758489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005967246,"about_ca_system_score_gemma":0.0008793992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008240165,"about_ca_topic_score_gemma":0.001497264,"domain_scores_codex":[0.99783,0.00002525676,0.000285365,0.0002451153,0.0002768969,0.001337406],"domain_scores_gemma":[0.9995964,0.0000634008,0.00007888522,0.0001224851,0.0001122982,0.00002651033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004487432,0.0002433008,0.05054477,0.0001589028,0.0005448913,0.0003926537,0.0001568146,0.0003928951,0.01921224,0.1516426,0.04862836,0.7276338],"study_design_scores_gemma":[0.0008678965,0.0001123912,0.004187247,0.0003786238,0.001138631,0.00616117,0.002431169,0.05168138,0.0003130113,0.02519297,0.9064321,0.001103443],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7852418,0.002124155,0.1835751,0.004070416,0.008440806,0.0004079448,0.000001140978,0.0004067977,0.01573185],"genre_scores_gemma":[0.9950536,0.0001458944,0.0003441621,0.0004258989,0.002229382,0.000004348243,0.000002762143,0.00003938518,0.001754606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8578037,"threshold_uncertainty_score":0.6597576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03224566925254647,"score_gpt":0.3223774053753745,"score_spread":0.2901317361228281,"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."}}