{"id":"W1916909999","doi":"10.1002/cjs.11187","title":"A new replicate variance estimator for unequal probability sampling without replacement","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Replicate; Estimator; Population variance; Statistics; Variance (accounting); Mathematics; Sampling (signal processing); Consistency (knowledge bases); Sampling design; Efficient estimator; Bias of an estimator; Consistent estimator; Minimum-variance unbiased estimator; Population; Econometrics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001213683,0.0001506246,0.0003255862,0.0001277341,0.0001686551,0.0001337567,0.0002216016,0.00007471222,0.000213898],"category_scores_gemma":[0.006165455,0.0001398498,0.00005944701,0.0001041233,0.00005477798,0.000139359,0.000008947209,0.0001757538,0.00001031751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002400809,"about_ca_system_score_gemma":0.001603478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004023624,"about_ca_topic_score_gemma":0.002501401,"domain_scores_codex":[0.9985171,0.00005300717,0.0007590274,0.0001707126,0.0001766737,0.0003234809],"domain_scores_gemma":[0.9967468,0.0009062038,0.0005516598,0.0003260915,0.0008167437,0.00065247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001363829,0.00008225031,0.01341509,0.000693723,0.0002160539,0.00001601071,0.001577603,0.0006319049,0.0001726522,0.4242862,0.487367,0.07140511],"study_design_scores_gemma":[0.0005234662,0.000293536,0.001801403,0.0001970646,0.00006598754,0.00005068988,0.00006118036,0.004618149,0.0002075134,0.9857472,0.006206634,0.0002271332],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006285822,0.00003591202,0.9920319,0.000495447,0.0002286076,0.0005502379,0.0002142252,0.00003339411,0.0001243944],"genre_scores_gemma":[0.06159472,0.000002672785,0.9378567,0.00008419472,0.0001196012,0.00002938168,0.00001207853,0.00003094969,0.0002697093],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5614611,"threshold_uncertainty_score":0.7381071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1631710627063437,"score_gpt":0.3555048550044894,"score_spread":0.1923337922981457,"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."}}