{"id":"W4254364319","doi":"10.1515/iupac.85.0700","title":"Relative Detection Limit","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Chemical nomenclature; Terminology; Mass spectrometry; Chemistry; Accelerator mass spectrometry; Analytical Chemistry (journal); Environmental chemistry; Chromatography; 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":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002254633,0.0004811367,0.0008255233,0.0004953154,0.0003025817,0.0002187877,0.001145413,0.00046313,0.002427414],"category_scores_gemma":[0.04851884,0.0003149905,0.0001933809,0.0007577791,0.0003113008,0.0006027746,0.0003840698,0.0009017015,0.00005365105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007281234,"about_ca_system_score_gemma":0.000472061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002809932,"about_ca_topic_score_gemma":0.0004464566,"domain_scores_codex":[0.9920965,0.0002675404,0.001167501,0.001151407,0.004780021,0.0005369621],"domain_scores_gemma":[0.9917881,0.003701072,0.0008139,0.001292103,0.002109129,0.0002956713],"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":[0.0001408087,0.00004829149,0.000003752244,0.00001549194,0.00003075065,0.00004750616,0.00001019535,0.00001030679,0.0000112433,0.00003985313,0.8844764,0.1151654],"study_design_scores_gemma":[0.0004195176,0.0002093233,0.00003911032,0.0001693966,0.0000499308,0.000009135345,0.00004389543,0.00003226432,0.00007038209,0.06118694,0.9373813,0.000388856],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001003351,0.0003038413,0.1914371,0.0002595324,0.001935081,0.0001946159,0.8056794,0.00006648743,0.0001139421],"genre_scores_gemma":[0.0003981487,0.0002414343,0.000795547,0.0001002473,0.001846384,0.00002440797,0.9946429,0.00005017398,0.001900743],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1906415,"threshold_uncertainty_score":0.9999302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07527698809676948,"score_gpt":0.5273549613550249,"score_spread":0.4520779732582554,"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."}}