{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006217014,0.0001008351,0.0001390021,0.0009010043,0.00007986619,0.00004185054,0.0001219404,0.00008743429,0.00004056284],"category_scores_gemma":[0.001052521,0.00009386849,0.00005548689,0.002394259,0.00002929503,0.00005964688,0.00003255848,0.00007319105,0.00005502031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006145189,"about_ca_system_score_gemma":0.0000257718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008045082,"about_ca_topic_score_gemma":0.000005668208,"domain_scores_codex":[0.9991734,0.00003015034,0.0002338685,0.0001529488,0.0002303699,0.0001792655],"domain_scores_gemma":[0.9986134,0.0009224286,0.0000993924,0.0002042249,0.0001255606,0.00003495357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006669637,0.00121093,0.02536292,0.0002458992,0.0001022929,0.00001821638,0.0002058155,0.00008625613,0.009529148,0.5895335,0.2195154,0.154123],"study_design_scores_gemma":[0.0007426996,0.0002170045,0.01654248,0.00009244306,0.00006090942,0.00002069223,0.0001060298,0.007093769,0.01491876,0.9007625,0.05857314,0.0008695485],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1147171,0.0002860928,0.8688769,0.0000704332,0.0002537638,0.0001814881,0.00004372298,0.001080218,0.01449028],"genre_scores_gemma":[0.6407796,0.000008886102,0.3586218,0.0000199468,0.0001072109,0.000009139138,0.00001233254,0.00001811081,0.0004229357],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5260625,"threshold_uncertainty_score":0.3827846,"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."}}