{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03029594,0.001325981,0.002064344,0.0022841,0.00091335,0.001619205,0.002848875,0.002316564,0.004721597],"category_scores_gemma":[0.1254474,0.0008552501,0.002008386,0.002117441,0.003439591,0.003107373,0.004607625,0.004364992,0.001130529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001500921,"about_ca_system_score_gemma":0.002163465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0019379,"about_ca_topic_score_gemma":0.001333104,"domain_scores_codex":[0.9781991,0.01813415,0.0004812623,0.001028897,0.0018953,0.0002613596],"domain_scores_gemma":[0.8960336,0.08725179,0.00398714,0.008836591,0.0033284,0.0005625089],"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":[0.0002416642,0.00008100449,0.003545293,0.0004671322,0.0002217136,0.0004838646,0.0004309688,0.2833242,0.001004597,0.6339444,0.00315425,0.0731009],"study_design_scores_gemma":[0.00003009711,0.00006095795,0.0004729193,0.0001331505,0.0000248414,0.0001474958,0.00003181866,0.5823343,0.0004498491,0.4124083,0.003879578,0.0000266669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002109617,0.0002249117,0.9960423,0.000208386,0.00003610516,0.00005503773,0.0000599555,0.0001637763,0.001099961],"genre_scores_gemma":[0.2697123,0.001625155,0.7208339,0.0006062326,0.0003485301,0.001545234,0.0007506118,0.0003650817,0.004212869],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03029594,"threshold_uncertainty_score":0.1602222,"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."}}