{"id":"W4382202359","doi":"10.1002/cjs.11777","title":"Nonparametric simulation extrapolation for measurement‐error models","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Waterloo; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Extrapolation; Nonparametric statistics; Replicate; Observational error; Normality; Computer science; Errors-in-variables models; Extension (predicate logic); Algorithm; Econometrics; Statistics; Mathematics; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02764911,0.00122999,0.002145885,0.002151906,0.0007182091,0.001096532,0.002567369,0.001844194,0.003772252],"category_scores_gemma":[0.1132248,0.0007080454,0.001804059,0.001724362,0.002516367,0.002088439,0.004145854,0.003605342,0.0007875902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001310742,"about_ca_system_score_gemma":0.001580002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002578548,"about_ca_topic_score_gemma":0.001422643,"domain_scores_codex":[0.9866599,0.0112255,0.0002996732,0.0005020552,0.001098767,0.0002140161],"domain_scores_gemma":[0.8854474,0.09927426,0.003440684,0.007361328,0.00383951,0.0006367321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003311033,0.0001062664,0.003831343,0.0003205365,0.000143652,0.000527344,0.0003420461,0.6594914,0.0007534573,0.2736273,0.002020763,0.05850476],"study_design_scores_gemma":[0.00001595089,0.00004813066,0.0003210106,0.00008862111,0.00001223501,0.00007482771,0.00002058589,0.8607954,0.0002417429,0.1370648,0.001301221,0.00001552972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006420234,0.000255784,0.9910019,0.0002026434,0.00004154665,0.0001000209,0.00006882678,0.0002305801,0.001678381],"genre_scores_gemma":[0.5153087,0.001136476,0.4771475,0.0004479923,0.0001893365,0.001189272,0.0006477675,0.0002530354,0.003679927],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02764911,"threshold_uncertainty_score":0.1462242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2878061622943208,"score_gpt":0.3956340640213991,"score_spread":0.1078279017270783,"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."}}