{"id":"W2074124346","doi":"10.1080/01621459.2014.922777","title":"Functional and Structural Methods With Mixed Measurement Error and Misclassification in Covariates","year":2014,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute of Environmental Health Sciences; National Institute of Allergy and Infectious Diseases; National Institute of Diabetes and Digestive and Kidney Diseases; National Cancer Institute","keywords":"Covariate; Inference; Observational error; Computer science; Econometrics; Statistics; Data mining; Machine learning; Mathematics; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002476502,0.00009916059,0.0003368797,0.00004600491,0.00007529178,0.00002972606,0.00005594631,0.00002734369,0.000005705826],"category_scores_gemma":[0.008894694,0.00005842116,0.00002331585,0.0001250246,0.0001244696,0.00007655216,0.00002303267,0.0002170682,1.601565e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002283607,"about_ca_system_score_gemma":0.00003960276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000181416,"about_ca_topic_score_gemma":0.00003178983,"domain_scores_codex":[0.9979839,0.0008944045,0.0003900399,0.0001202346,0.0004704991,0.0001409573],"domain_scores_gemma":[0.9951895,0.003489459,0.0008900358,0.00007657511,0.0002805778,0.00007382307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007585834,0.000141432,0.03717495,0.0000954873,0.0002738117,0.000003095129,0.0005295379,0.000276056,0.006895536,0.5974861,0.00106225,0.3553032],"study_design_scores_gemma":[0.0005606278,0.0002098163,0.4863452,0.00003340931,0.0001018892,0.00001597696,0.0001223933,0.01237358,0.0001136571,0.4999399,0.0001007564,0.00008273162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08166893,0.00001680777,0.9168915,0.001205018,0.00008100448,0.00008276765,0.00001220605,0.000004063216,0.00003777194],"genre_scores_gemma":[0.4436207,0.000004321997,0.5562577,0.00006082225,0.00003248961,0.000002205254,4.225436e-7,0.000006309517,0.00001501708],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4491703,"threshold_uncertainty_score":0.9994538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09363819307541298,"score_gpt":0.4062871231973908,"score_spread":0.3126489301219778,"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."}}