{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001786875,0.0001194899,0.0002900528,0.0005520686,0.0001426261,0.00007853103,0.0001570103,0.00007440562,0.0001020107],"category_scores_gemma":[0.0120007,0.0001098856,0.00007020366,0.0005186693,0.00005106092,0.0001336795,0.000004408531,0.0001389137,0.000008222148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001907301,"about_ca_system_score_gemma":0.0007643726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001348869,"about_ca_topic_score_gemma":0.00119667,"domain_scores_codex":[0.9983649,0.0000964688,0.0006922017,0.0001131968,0.0004230085,0.0003102841],"domain_scores_gemma":[0.9950897,0.002646344,0.0003972805,0.0001375077,0.001328578,0.000400659],"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":[0.00002508342,0.00001484125,0.0002322678,0.0001262526,0.00005405454,0.00004446677,0.0003760677,0.007681464,0.0000361963,0.8893195,0.02374247,0.07834735],"study_design_scores_gemma":[0.000244963,0.00009632821,0.0008354515,0.00003981944,0.00005512213,0.000005251388,0.00005238265,0.3169646,0.00001304066,0.68075,0.0008541567,0.00008891417],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005948385,0.00003460533,0.997645,0.0001142082,0.0004132719,0.0002140551,0.000684326,0.00001113888,0.0002885704],"genre_scores_gemma":[0.3482358,0.000003437746,0.651557,0.00003011771,0.00009841097,0.000003757235,0.000008853352,0.000019703,0.00004287749],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.347641,"threshold_uncertainty_score":0.9963216,"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."}}