{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001378346,0.0005717755,0.0007406988,0.0002719002,0.0001739956,0.0002935994,0.002055861,0.0005086017,0.000363354],"category_scores_gemma":[0.0003876781,0.0004141813,0.0002578504,0.0002527514,0.0001012569,0.0003224826,0.0008916665,0.0006501262,0.000004653671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00029401,"about_ca_system_score_gemma":0.0006246484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005587514,"about_ca_topic_score_gemma":0.0001625311,"domain_scores_codex":[0.9963362,0.000249827,0.0005947771,0.001044153,0.001093201,0.000681908],"domain_scores_gemma":[0.9965617,0.0002755628,0.0003311344,0.002152496,0.0003950388,0.0002840379],"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":[0.0000202465,0.00007093919,3.475967e-7,0.00007682667,0.00004124188,0.00005058145,0.00001903466,8.867723e-7,0.000009613958,0.0007024005,0.9183881,0.08061978],"study_design_scores_gemma":[0.0007562893,0.00008944793,0.000003782886,0.0003297368,0.00003423767,0.00003192864,0.000001163913,0.0003312584,0.00001898298,0.005098991,0.9927244,0.0005798496],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[5.430373e-7,0.0003048741,0.4970136,0.0005772033,0.0008943877,0.0001620604,0.5009252,0.00008703896,0.00003508478],"genre_scores_gemma":[9.282433e-7,0.000349658,0.2218538,0.001141636,0.0009125135,0.00001382725,0.7750914,0.00003369231,0.0006025458],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2751598,"threshold_uncertainty_score":0.999831,"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."}}