{"id":"W2052097769","doi":"10.1093/biomet/87.4.929","title":"Empirical likelihood inference under stratified random sampling using auxiliary population information","year":2000,"lang":"en","type":"article","venue":"Biometrika","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Mathematics; Stratified sampling; Inference; Population; Statistics; Library science; Sampling (signal processing); Demography; Computer science; Artificial intelligence; Sociology; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.05522585,0.001214521,0.003780858,0.00385532,0.001133168,0.003621932,0.00348776,0.002219302,0.007626579],"category_scores_gemma":[0.2745198,0.001635778,0.00329106,0.004843228,0.003440948,0.00512281,0.003591853,0.003596395,0.001761154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00244107,"about_ca_system_score_gemma":0.003946584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006054476,"about_ca_topic_score_gemma":0.004324883,"domain_scores_codex":[0.9484553,0.04355304,0.001158,0.002733099,0.003238985,0.0008616298],"domain_scores_gemma":[0.7704386,0.199767,0.006908847,0.01610981,0.005787927,0.0009878946],"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":[0.000670907,0.0002023964,0.01611752,0.0007622103,0.001024651,0.0004790382,0.0008645216,0.1405049,0.0005097031,0.7118511,0.009980055,0.1170331],"study_design_scores_gemma":[0.0001874518,0.0001477635,0.002705491,0.0002430664,0.0002203607,0.0002032165,0.0001419715,0.4096388,0.0005715847,0.5825796,0.003306763,0.00005397257],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01303088,0.0005346618,0.9826115,0.0006048583,0.00008033403,0.0002341666,0.0004575899,0.0002554423,0.002190661],"genre_scores_gemma":[0.4334057,0.002213759,0.552884,0.0007705264,0.0004464129,0.00197144,0.003545864,0.0002225251,0.00453979],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05522585,"threshold_uncertainty_score":0.2920657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2299445286686772,"score_gpt":0.4337713915434576,"score_spread":0.2038268628747805,"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."}}