{"id":"W4408977537","doi":"10.1016/j.trc.2025.105105","title":"Corrigendum to “Copula-based transferable models for synthetic population generation” [Transp. Res. Part C 169 (2024) 104830]","year":2025,"lang":"en","type":"erratum","venue":"Transportation Research Part C Emerging Technologies","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Ministerio de Ciencia e Innovación; Albert Ellis Institute","keywords":"Copula (linguistics); Econometrics; Computer science; Mathematics","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"],"consensus_categories":[],"category_scores_codex":[0.001967936,0.0005731814,0.0006786456,0.0007745992,0.001283854,0.0001472502,0.0009978754,0.0009854131,0.0004261776],"category_scores_gemma":[0.0004247942,0.0006009972,0.000284313,0.001649046,0.0003534904,0.0003390425,0.00004069358,0.001548621,0.00005296709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005678875,"about_ca_system_score_gemma":0.0001854142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002201932,"about_ca_topic_score_gemma":0.003559798,"domain_scores_codex":[0.9943349,0.0002078696,0.001111664,0.001467842,0.001575586,0.001302175],"domain_scores_gemma":[0.9982314,0.0001904433,0.0001813377,0.001026622,0.0002097888,0.0001604155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009076767,0.0001119042,0.0006729221,0.000562813,0.00005104855,0.00001195313,0.0003937544,0.08437983,0.0002406081,0.001114562,0.8882342,0.02413565],"study_design_scores_gemma":[0.0004910174,0.0003997184,0.0003300514,0.001279866,0.0001254009,3.995569e-7,0.0007304199,0.07464875,0.002999491,0.005242834,0.9128182,0.0009338421],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.03489712,0.005048562,0.7065262,0.06333336,0.1170143,0.02530545,0.008069141,0.01371871,0.0260872],"genre_scores_gemma":[0.2361853,0.002717262,0.03487381,0.0003095682,0.001955922,0.01123055,0.01522546,0.0004963249,0.6970058],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6716523,"threshold_uncertainty_score":0.9996442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1528267302633609,"score_gpt":0.3658800573956503,"score_spread":0.2130533271322893,"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."}}