{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007423063,0.002162967,0.003162169,0.007148419,0.000953897,0.005698805,0.004190987,0.002320092,0.07181112],"category_scores_gemma":[0.04494758,0.0007215601,0.002660111,0.009439932,0.0007254516,0.004151327,0.001939057,0.002850823,0.08322696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002253221,"about_ca_system_score_gemma":0.002903195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008872177,"about_ca_topic_score_gemma":0.008611032,"domain_scores_codex":[0.9843735,0.002322287,0.002122771,0.004730535,0.005886551,0.0005644083],"domain_scores_gemma":[0.9774342,0.008562082,0.002251805,0.003396415,0.008059152,0.0002962675],"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":[0.0005792514,0.0001271659,0.009464695,0.005127221,0.0003784273,0.00009929604,0.00009977237,0.001699353,0.001784951,0.006987309,0.851678,0.1219745],"study_design_scores_gemma":[0.0001539345,0.00008234581,0.00846309,0.001071491,0.0002049651,0.0002803227,0.0001594363,0.002237183,0.004975206,0.01484967,0.9673735,0.0001488337],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002862005,0.008557365,0.01530897,0.0009896214,0.001117583,0.0004369828,0.938502,0.005351156,0.02687442],"genre_scores_gemma":[0.02266717,0.007226453,0.03821154,0.002195466,0.0005733983,0.002495254,0.9051971,0.001886325,0.01954727],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07181112,"threshold_uncertainty_score":0.2402322,"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."}}