{"id":"W1979604055","doi":"10.1002/cjs.11237","title":"Generalized pseudo empirical likelihood inferences for complex surveys","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Empirical likelihood; Statistics; Mathematics; Estimator; Weighting; Statistic; Confidence interval; Calibration; Confidence distribution; Applied mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.02259507,0.0009837399,0.001506609,0.002770182,0.000576209,0.00263394,0.002726902,0.001582564,0.005324455],"category_scores_gemma":[0.1717342,0.0006095556,0.001342294,0.003121741,0.003337738,0.005461292,0.003341646,0.002308782,0.0005923937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001380489,"about_ca_system_score_gemma":0.001159626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001807349,"about_ca_topic_score_gemma":0.001294659,"domain_scores_codex":[0.9798895,0.01651392,0.0004678769,0.001218429,0.00168409,0.00022615],"domain_scores_gemma":[0.8732315,0.1077164,0.006175902,0.008524476,0.003733769,0.000617898],"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":[0.0001376376,0.00004729538,0.003638567,0.0003051769,0.0002701988,0.0002937496,0.0002877938,0.2662076,0.000504511,0.6456744,0.002313826,0.0803193],"study_design_scores_gemma":[0.00004369996,0.00004991397,0.001223268,0.00006656335,0.00003190895,0.0001175235,0.00006272985,0.5278386,0.0004399422,0.4676121,0.002476599,0.00003725251],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01153323,0.0002862398,0.986222,0.0002490552,0.00003316289,0.0000577493,0.00008626378,0.0001113748,0.001420913],"genre_scores_gemma":[0.5584334,0.0009452608,0.4366556,0.0005432562,0.0001983706,0.000402537,0.0004436414,0.0001466981,0.00223115],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02259507,"threshold_uncertainty_score":0.1194956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2740594724168929,"score_gpt":0.4136428448665517,"score_spread":0.1395833724496587,"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."}}