{"id":"W4249469497","doi":"10.1515/iupac.76.0376","title":"Sampling Error","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Relation (database); Hazard; Computer science; Toxicology; Medicine; Data mining; Chemistry; Pharmacology; Biology; 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":[0.01888162,0.001896623,0.002302858,0.004244293,0.001556551,0.003843738,0.004372165,0.002257065,0.09829022],"category_scores_gemma":[0.1353246,0.0008870169,0.002996246,0.007308124,0.001302119,0.002159829,0.003034937,0.003039991,0.06998792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002376127,"about_ca_system_score_gemma":0.003398592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009303396,"about_ca_topic_score_gemma":0.01211432,"domain_scores_codex":[0.9707601,0.008854224,0.006582001,0.007944808,0.004820326,0.001038472],"domain_scores_gemma":[0.9256435,0.03483693,0.005406613,0.0228186,0.01056946,0.0007249452],"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":[0.0004466912,0.00009649769,0.008415699,0.001603838,0.0002600488,0.00008665982,0.0001574434,0.001336711,0.0001441867,0.004487135,0.9474559,0.03550922],"study_design_scores_gemma":[0.0008300645,0.00008716261,0.01051455,0.00142756,0.0002470405,0.000265717,0.0001892511,0.002399646,0.0007423041,0.01330468,0.9698855,0.0001064739],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003256435,0.001203051,0.0122874,0.0007981151,0.001140793,0.001163402,0.9704534,0.002193956,0.007503485],"genre_scores_gemma":[0.01401364,0.0004514216,0.0112223,0.001291184,0.0003073912,0.007318274,0.9546905,0.001008549,0.009696764],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09829022,"threshold_uncertainty_score":0.3288136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1431271857106665,"score_gpt":0.567327985441789,"score_spread":0.4242007997311225,"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."}}