{"id":"W2140207798","doi":"10.1093/annhyg/mei073","title":"Metamodels of bias in Cox proportional-hazards and logistic regressions with heteroscedastic measurement error under group-level exposure assessment","year":2005,"lang":"en","type":"article","venue":"The Annals of Occupational Hygiene","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Logistic regression; Statistics; Heteroscedasticity; Proportional hazards model; Group (periodic table); Environmental science; Econometrics; Environmental health; Mathematics; Medicine; Chemistry","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05946876,0.0009558889,0.001729087,0.001406673,0.0006699354,0.001797072,0.002539287,0.00246632,0.001972961],"category_scores_gemma":[0.1605223,0.0008069925,0.002382113,0.001423672,0.002021319,0.002433875,0.001961613,0.002627732,0.0003786843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00183014,"about_ca_system_score_gemma":0.001648226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003407425,"about_ca_topic_score_gemma":0.002551232,"domain_scores_codex":[0.9770496,0.01950412,0.0005741209,0.001319433,0.001065288,0.0004875152],"domain_scores_gemma":[0.8170077,0.1656691,0.007575924,0.006333705,0.002771677,0.0006418894],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005766683,0.0001148825,0.0129368,0.00018821,0.0004440439,0.0002701153,0.0005131952,0.7810569,0.0005184828,0.1784822,0.0007873594,0.02411124],"study_design_scores_gemma":[0.0001210187,0.0001755322,0.001442463,0.00006048132,0.00008932092,0.00009837481,0.000055627,0.8314511,0.0004240052,0.1651773,0.0008591503,0.00004566519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0690245,0.0005010699,0.9278396,0.0008813856,0.00008331642,0.0001769532,0.0002452162,0.000230994,0.001016933],"genre_scores_gemma":[0.7929699,0.0006471121,0.2022079,0.0004703483,0.00009979247,0.0009524849,0.0004140236,0.00008598548,0.002152343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9405313,"threshold_uncertainty_score":0.3145046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6674840167960389,"score_gpt":0.5270307177163275,"score_spread":0.1404532990797114,"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."}}