{"id":"W2132467996","doi":"10.1111/j.1541-0420.2006.00576.x","title":"Adaptive Web Sampling","year":2006,"lang":"en","type":"article","venue":"Biometrics","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Los Alamos National Laboratory; National Science Foundation","keywords":"Resampling; Computer science; Inference; Sampling (signal processing); Markov chain; Sampling design; Sample (material); Statistic; Population; Markov chain Monte Carlo; Adaptive sampling; Data mining; Statistics; Machine learning; Artificial intelligence; Mathematics; 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":[0.01697115,0.0009623395,0.001419522,0.002218868,0.001082081,0.001530601,0.003322726,0.001458745,0.009346928],"category_scores_gemma":[0.05043092,0.0008088131,0.001408578,0.002365142,0.001803103,0.002077869,0.002764339,0.001821214,0.00184374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007583405,"about_ca_system_score_gemma":0.001505613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001420161,"about_ca_topic_score_gemma":0.001649464,"domain_scores_codex":[0.9842461,0.01152407,0.0005181072,0.001542626,0.001825016,0.0003441558],"domain_scores_gemma":[0.9643092,0.02350575,0.001412687,0.008132201,0.002155055,0.000485123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009892181,0.0003833421,0.01057429,0.0004760671,0.0003647267,0.0002810527,0.000541248,0.09835505,0.003961148,0.372234,0.007605053,0.5042349],"study_design_scores_gemma":[0.0005421258,0.000743594,0.003214873,0.0001783702,0.0001545262,0.0004999302,0.0001170927,0.6261024,0.003411998,0.3376431,0.02729887,0.00009306549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003491106,0.0000932135,0.9943539,0.00004245093,0.00004961024,0.0003514964,0.0001353094,0.000244952,0.00123799],"genre_scores_gemma":[0.1607119,0.0003615947,0.8290717,0.0002681283,0.0001857493,0.004095926,0.0006742667,0.0001587039,0.004472117],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01697115,"threshold_uncertainty_score":0.08975315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.241440605869536,"score_gpt":0.3821246386598277,"score_spread":0.1406840327902917,"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."}}