{"id":"W7096259359","doi":"","title":"AN APPLICATION OF THE BOOTSTRAP VARIANCE ESTIMATION METHOD TO THE PARTICIPATION AND ACTIVITY LIMITATION SURVEY","year":2015,"lang":"en","type":"article","venue":"","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Jackknife resampling; Logistic regression; Variance (accounting); Sampling (signal processing); Propensity score matching; Stratified sampling; Sampling design; Range (aeronautics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03019401,0.0008228712,0.001505589,0.003933611,0.0008861746,0.0009995555,0.001679729,0.001212169,0.004910464],"category_scores_gemma":[0.1296226,0.0006371611,0.001711756,0.004996473,0.001448815,0.00112488,0.0023706,0.002188761,0.001116695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009815113,"about_ca_system_score_gemma":0.002501902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005087704,"about_ca_topic_score_gemma":0.005727376,"domain_scores_codex":[0.9617589,0.03315717,0.0006932654,0.0009769257,0.003131206,0.0002824885],"domain_scores_gemma":[0.9523749,0.03861429,0.001824545,0.003510007,0.003382984,0.0002931895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003146334,0.0002460802,0.0155723,0.0007610066,0.0007536347,0.0005915866,0.001376395,0.02782085,0.001692607,0.1850269,0.02110025,0.7447436],"study_design_scores_gemma":[0.0003822569,0.0008307885,0.02814295,0.001128755,0.0004040253,0.001479076,0.0008137923,0.3673075,0.00306118,0.5055683,0.09059535,0.0002861345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002831436,0.0002311044,0.9948775,0.0003050244,0.00009103199,0.0002177202,0.0001335467,0.0002435206,0.001069056],"genre_scores_gemma":[0.08934057,0.0007159185,0.9053017,0.0003427136,0.0002451956,0.001865559,0.0004278202,0.0002297719,0.001530738],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03019401,"threshold_uncertainty_score":0.1596831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2642780162916235,"score_gpt":0.4922430272673661,"score_spread":0.2279650109757426,"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."}}