{"id":"W3033397941","doi":"10.15388/lmr.2008.18112","title":"Estimation of employed persons in the case of sample rotation","year":2008,"lang":"en","type":"article","venue":"Lietuvos matematikos rinkinys","topic":"Agricultural economics and policies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Simple random sample; Statistics; Rotation (mathematics); Sample (material); Mathematics; Sampling design; Variance (accounting); Sampling (signal processing); Bias of an estimator; Minimum-variance unbiased estimator; Estimation; Quarter (Canadian coin); Econometrics; Computer science; Engineering; Geography; Population; Economics; Sociology","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":[0.01699444,0.0003697397,0.001079709,0.001015851,0.0002836312,0.000978227,0.00107835,0.0008814579,0.00178145],"category_scores_gemma":[0.07371185,0.0003251168,0.0008237676,0.0009028728,0.0008495111,0.001080478,0.001121788,0.0004855505,0.0003540325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000389746,"about_ca_system_score_gemma":0.0005235426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002258375,"about_ca_topic_score_gemma":0.0008677432,"domain_scores_codex":[0.9859338,0.01146189,0.0003634166,0.001102648,0.0007046402,0.0004336166],"domain_scores_gemma":[0.9643819,0.02778268,0.003527103,0.003111616,0.001004647,0.0001920585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001814302,0.0003483852,0.4224657,0.0006436768,0.001137957,0.002216296,0.001100039,0.2340903,0.005209428,0.1000339,0.001858786,0.2290813],"study_design_scores_gemma":[0.0001838695,0.0008940729,0.07484056,0.00009125842,0.0003867865,0.001464117,0.0006379057,0.8805833,0.005714874,0.03126895,0.003864875,0.00006934356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5641334,0.001256902,0.4313134,0.0003997589,0.00005307331,0.0001417214,0.000243207,0.0001216864,0.002336895],"genre_scores_gemma":[0.9463079,0.0004634952,0.05195428,0.00004142779,0.00006109606,0.00005560043,0.0002327434,0.00001440158,0.0008690896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01699444,"threshold_uncertainty_score":0.08987629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03247926734120143,"score_gpt":0.2950764216330006,"score_spread":0.2625971542917992,"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."}}