{"id":"W2159528252","doi":"10.1111/1467-9868.00277","title":"On Measuring Sensitivity to Parametric Model Misspecification","year":2001,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series B (Statistical Methodology)","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Parametric statistics; Sensitivity (control systems); Inference; Parametric model; Measure (data warehouse); Econometrics; Mathematics; Sample (material); Distribution (mathematics); Statistics; Sample size determination; Computer science; Physics; Artificial intelligence; Data mining","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":[0.144302,0.001561146,0.002575282,0.004952944,0.001310773,0.003569406,0.003347651,0.003404388,0.002133117],"category_scores_gemma":[0.6211388,0.001053278,0.002403004,0.004380989,0.007817557,0.006851907,0.006519978,0.006793709,0.0003706741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002757776,"about_ca_system_score_gemma":0.001692496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002126922,"about_ca_topic_score_gemma":0.001002807,"domain_scores_codex":[0.8418109,0.1190718,0.006839485,0.01344443,0.01749764,0.001335806],"domain_scores_gemma":[0.1225509,0.8114011,0.03058718,0.02769605,0.006592945,0.001171848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002036162,0.0001962034,0.1031854,0.0009661147,0.00391247,0.001709479,0.001874838,0.6852927,0.003842624,0.09310129,0.002510474,0.1013722],"study_design_scores_gemma":[0.00007817636,0.0008782914,0.0330097,0.0005230579,0.0007138028,0.002244401,0.0006240308,0.6436356,0.006133805,0.3095822,0.002250981,0.0003259572],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1744612,0.002775505,0.8140369,0.002217337,0.0001571968,0.000247763,0.0004738107,0.0005760948,0.005054154],"genre_scores_gemma":[0.896461,0.000517037,0.1003764,0.0009606295,0.0002025291,0.0002006301,0.0005360271,0.0002793166,0.0004665068],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.144302,"threshold_uncertainty_score":0.7631511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2678161307297549,"score_gpt":0.3996099280758321,"score_spread":0.1317937973460772,"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."}}