{"id":"W4253133166","doi":"10.1515/iupac.79.1657","title":"Multistage Cluster Sampling","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Toxicology; Chemistry; Biology; Philosophy; Linguistics","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":[0.007147771,0.002998838,0.00279173,0.004431009,0.001784081,0.003225558,0.007101087,0.002674469,0.03828154],"category_scores_gemma":[0.02690799,0.0009041508,0.004298696,0.006121957,0.0009346664,0.001428331,0.00255557,0.003285699,0.04283872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002693274,"about_ca_system_score_gemma":0.005286269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02417721,"about_ca_topic_score_gemma":0.0563508,"domain_scores_codex":[0.9942139,0.001912225,0.0007032414,0.001813291,0.0008861182,0.0004711408],"domain_scores_gemma":[0.9920604,0.002835767,0.0003965485,0.002562774,0.001799751,0.000344729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006941166,0.0002632889,0.005634824,0.001624287,0.0003642334,0.00009753282,0.00008426268,0.005207684,0.0002255352,0.002204941,0.9468744,0.03672496],"study_design_scores_gemma":[0.002628982,0.0003274966,0.01345071,0.001154337,0.0005865236,0.0004895847,0.0003917015,0.03601816,0.002139366,0.01870231,0.9239073,0.0002034746],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0029915,0.0007465802,0.005769612,0.0003779043,0.0003625251,0.0008075791,0.984641,0.002104829,0.002198442],"genre_scores_gemma":[0.003770256,0.0002065741,0.01120963,0.0001874253,0.00005290205,0.001521501,0.9803268,0.0001905838,0.002534402],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03828154,"threshold_uncertainty_score":0.1280645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02603571518015014,"score_gpt":0.4231488185778554,"score_spread":0.3971131033977053,"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."}}