{"id":"W4241396882","doi":"10.1515/iupac.78.0366","title":"Impurity","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Pesticide; Management science; Data science; Environmental chemistry; Chemistry; Engineering; Ecology; Biology; Data mining","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":[0.001441915,0.001808301,0.001261956,0.005557091,0.001135517,0.003318954,0.002848314,0.002094906,0.1549493],"category_scores_gemma":[0.01113191,0.0005679985,0.001531202,0.008914181,0.0004934128,0.002836376,0.002273008,0.001983859,0.1777811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002263152,"about_ca_system_score_gemma":0.003418481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0240413,"about_ca_topic_score_gemma":0.04590762,"domain_scores_codex":[0.99751,0.0004037455,0.0004425239,0.0008447489,0.0005382088,0.0002608621],"domain_scores_gemma":[0.9958615,0.00114562,0.0005042438,0.0008788994,0.001349317,0.0002605592],"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":[0.00004919455,0.00001525299,0.000878727,0.00069263,0.00001888198,0.00001995908,0.0000310186,0.000127129,0.00009046702,0.0009688539,0.9930887,0.004019202],"study_design_scores_gemma":[0.00006994869,0.000009861106,0.002104737,0.000460423,0.00001712154,0.00005452745,0.00008336858,0.0001624369,0.000148197,0.001300528,0.9955682,0.00002078978],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008982586,0.00008138884,0.00008700576,0.00009429222,0.00002295356,0.00001839203,0.9984085,0.0001464264,0.001051245],"genre_scores_gemma":[0.0002478464,0.00006818385,0.0002904059,0.00009224051,0.00000670681,0.0001039113,0.998261,0.0000507416,0.0008789753],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1549493,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581163172713638,"score_gpt":0.4296719265590623,"score_spread":0.4138602948319259,"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."}}