{"id":"W4312447901","doi":"10.2478/stattrans-2022-0010","title":"Variance estimation in stratified adaptive cluster sampling","year":2022,"lang":"en","type":"article","venue":"Statistics in Transition New Series","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Estimator; Cluster sampling; Stratified sampling; Statistics; Sampling (signal processing); Simple random sample; Sampling design; Variance (accounting); Mathematics; Population variance; Mean squared error; Multistage sampling; Population; Slice sampling; Importance sampling; Computer science; Monte Carlo method","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":[0.008503174,0.000513241,0.0009959888,0.001716869,0.0004447663,0.0008171257,0.001550284,0.0006424332,0.001529995],"category_scores_gemma":[0.02927699,0.0004781815,0.0008475541,0.001969002,0.001123961,0.0008395492,0.001392897,0.0008448919,0.0003302484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001207561,"about_ca_system_score_gemma":0.001581782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004815341,"about_ca_topic_score_gemma":0.003019522,"domain_scores_codex":[0.992366,0.004996612,0.0002200031,0.000812803,0.001338805,0.0002656894],"domain_scores_gemma":[0.9869654,0.007649454,0.001005879,0.001575841,0.002660477,0.0001429883],"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":[0.000546034,0.0001076264,0.01524172,0.0003814614,0.0003974875,0.0001793678,0.0005046218,0.4574033,0.007176732,0.2834808,0.002548279,0.2320326],"study_design_scores_gemma":[0.00002982157,0.000115288,0.002733859,0.00004195232,0.0000507325,0.0000556461,0.00004393619,0.9362986,0.002751388,0.05566699,0.002184242,0.00002760923],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01151749,0.00009987331,0.9876353,0.00003134969,0.00001595761,0.00005432649,0.00003877932,0.00009590562,0.0005109462],"genre_scores_gemma":[0.4803139,0.0002298958,0.5169588,0.000103553,0.00005829581,0.0003542379,0.0002853231,0.00007445306,0.001621539],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008503174,"threshold_uncertainty_score":0.04496962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08296716982804798,"score_gpt":0.3468874436268825,"score_spread":0.2639202737988345,"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."}}