{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009144735,0.0005051824,0.0009572135,0.0001332984,0.0001359607,0.00003875152,0.0004192153,0.000396495,0.002430469],"category_scores_gemma":[0.007479011,0.0003548055,0.0001915887,0.0001070921,0.0001491264,0.00007388591,0.0002075736,0.0005702183,0.000002128532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000295568,"about_ca_system_score_gemma":0.0003629697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001400217,"about_ca_topic_score_gemma":0.0001315282,"domain_scores_codex":[0.9970346,0.000142784,0.000680745,0.0006118805,0.0009643064,0.000565702],"domain_scores_gemma":[0.9963733,0.001708752,0.0002361828,0.0009959989,0.0004418676,0.0002439183],"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":[0.00007782484,0.0001362333,1.03877e-7,0.0003082491,0.00006714519,0.00003718086,0.00000714278,0.0000010178,0.000009160256,0.004415961,0.9820275,0.01291247],"study_design_scores_gemma":[0.0004074999,0.00008820728,3.483605e-7,0.0004460834,0.00012135,0.000008425211,0.000009227697,0.00001143165,0.000007546812,0.2829257,0.7156205,0.0003537093],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002577398,0.000111698,0.4353295,0.0001465394,0.0003746608,0.0001894641,0.5637515,0.00006068083,0.00003336167],"genre_scores_gemma":[4.581971e-7,0.0002139763,0.1985111,0.0001482746,0.0007290104,0.00002024892,0.7999427,0.00006669528,0.0003675917],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2785097,"threshold_uncertainty_score":0.9998904,"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."}}