{"id":"W4319845000","doi":"10.1002/9781119672333.ch27","title":"Introduction to Sampling and Estimation for Business Surveys","year":2023,"lang":"en","type":"other","venue":"","topic":"Water Quality and Resources Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Sampling (signal processing); Variance (accounting); Stratified sampling; Sample (material); Sampling design; Estimation; Statistics; Computer science; Econometrics; Sample size determination; Survey sampling; Unbiased Estimation; Sampling bias; Data mining; Mathematics; Engineering; Population; Accounting; Estimator","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":[0.01878376,0.001900559,0.001568253,0.00298706,0.001104153,0.00259423,0.002606927,0.00303613,0.04321845],"category_scores_gemma":[0.06844691,0.001370757,0.00157491,0.007642727,0.00168391,0.00321904,0.002157717,0.004850623,0.01997861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001920149,"about_ca_system_score_gemma":0.00361536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007779005,"about_ca_topic_score_gemma":0.007721203,"domain_scores_codex":[0.9816573,0.0136181,0.0009768136,0.001050465,0.002463297,0.0002340669],"domain_scores_gemma":[0.9621751,0.0298398,0.001276764,0.003385743,0.003058032,0.0002646058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004391719,0.0001182064,0.003307112,0.001998582,0.000115974,0.0002433699,0.0005767865,0.01702542,0.0004261778,0.3994628,0.196525,0.3801565],"study_design_scores_gemma":[0.00004818532,0.0001060794,0.003659202,0.002063679,0.00005302453,0.0004992542,0.0002419936,0.03606837,0.0003641476,0.3975551,0.5592347,0.0001063595],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005489628,0.008664235,0.9581349,0.002533715,0.001177515,0.001189064,0.004427301,0.0008350144,0.02248928],"genre_scores_gemma":[0.01204952,0.02029975,0.9371389,0.001627574,0.002540094,0.00596834,0.004650941,0.0005971466,0.0151277],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04321845,"threshold_uncertainty_score":0.1445802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0696793934808756,"score_gpt":0.2789396490294049,"score_spread":0.2092602555485293,"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."}}