{"id":"W3209217553","doi":"10.48550/arxiv.2111.02863","title":"Nonparametric Simulation Extrapolation for Measurement Error Models","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Extrapolation; Nonparametric statistics; Replicate; Observational error; Computer science; Normality; Errors-in-variables models; Algorithm; Statistics; Mathematics; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006966873,0.0002775103,0.0004379551,0.000236594,0.0001212077,0.00008501238,0.000279952,0.0003315792,0.00008334975],"category_scores_gemma":[0.001525721,0.0003157069,0.0002470722,0.0004259143,0.00004849581,0.0001654923,0.0002036751,0.0003156943,0.000003299048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003457116,"about_ca_system_score_gemma":0.0001982926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003452675,"about_ca_topic_score_gemma":0.00002759038,"domain_scores_codex":[0.9982775,0.0002067814,0.0003200789,0.0007381171,0.0001842568,0.0002731942],"domain_scores_gemma":[0.9968501,0.001352286,0.0003141466,0.0005784155,0.0007850974,0.0001199614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006661207,0.0001546034,0.00008535432,0.0004365601,0.0001072108,0.00001648258,0.0001182705,0.4105538,0.00003073361,0.5846638,0.00005820183,0.003708336],"study_design_scores_gemma":[0.0002245363,0.00002294805,0.0000796322,0.00009443006,0.0001653477,2.361318e-7,0.00004482446,0.5109342,0.00003584855,0.4882036,0.00001202676,0.000182298],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01680324,0.00004478342,0.9809208,0.00001972298,0.0003061854,0.000757493,0.00006427467,0.00009448622,0.0009890116],"genre_scores_gemma":[0.7120981,0.00001481213,0.2876709,0.00001506288,0.00005256862,0.000004178204,0.00002338822,0.0000237435,0.00009731874],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6952949,"threshold_uncertainty_score":0.9999295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4678353682496953,"score_gpt":0.3193765392766447,"score_spread":0.1484588289730507,"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."}}