{"id":"W2904405044","doi":"10.1515/ijb-2017-0002","title":"Parametric Regression Analysis with Covariate Misclassification in Main Study/Validation Study Designs","year":2018,"lang":"en","type":"article","venue":"The International Journal of Biostatistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute of Environmental Health Sciences; National Cancer Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Covariate; Inference; Computer science; Statistics; Statistical inference; Observational error; Data mining; Econometrics; Causal inference; Parametric statistics; Nonparametric statistics; Machine learning; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002840966,0.0001487697,0.0003395664,0.0006513054,0.00008344802,0.0001437571,0.0005710092,0.0000371949,0.0001130331],"category_scores_gemma":[0.003580738,0.00008372525,0.0000514471,0.001113248,0.0001166144,0.0001015691,0.00005277144,0.0002307734,0.000005958093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000152853,"about_ca_system_score_gemma":0.0001109833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006521816,"about_ca_topic_score_gemma":0.0002276127,"domain_scores_codex":[0.9971356,0.0007283058,0.0008271491,0.0001740765,0.0009903173,0.0001445022],"domain_scores_gemma":[0.9947984,0.003023994,0.0008877973,0.0002516841,0.0009792111,0.00005890259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005356433,0.01205851,0.6249467,0.00004072696,0.008279947,0.001366476,0.01864543,0.0002911079,0.001987469,0.2237915,0.002930786,0.100305],"study_design_scores_gemma":[0.003594292,0.004331918,0.5483665,0.0001673545,0.002280653,0.0001042296,0.007708793,0.01035925,0.001333947,0.4213593,0.00003383227,0.0003599041],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3456414,0.000004002559,0.6536016,0.0002306283,0.0001756672,0.0002412162,0.00003121265,0.000005363186,0.00006894094],"genre_scores_gemma":[0.7411235,0.000005326479,0.2586906,0.00002725713,0.0001119801,0.000005366737,0.000003442581,0.00000971952,0.00002283036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3954821,"threshold_uncertainty_score":0.4286736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.163271307064427,"score_gpt":0.4423361246666251,"score_spread":0.2790648176021981,"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."}}