{"id":"W4241218513","doi":"10.1515/iupac.81.0922","title":"Trace Nutrient","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; TRACE (psycholinguistics); Environmental chemistry; Ecology; Environmental science; Computer science; Chemistry; Biology; Philosophy; 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":[0.001106914,0.001896158,0.001445223,0.0041243,0.001227751,0.003464301,0.003236158,0.002271345,0.06817497],"category_scores_gemma":[0.006861506,0.0005958942,0.001553022,0.005938102,0.0004331927,0.002486968,0.002485917,0.002192489,0.1048656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002201395,"about_ca_system_score_gemma":0.003504281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0322324,"about_ca_topic_score_gemma":0.06465156,"domain_scores_codex":[0.9986309,0.0001703587,0.0001689235,0.0004811782,0.0003885788,0.0001600248],"domain_scores_gemma":[0.9975775,0.0005656923,0.0002279152,0.0005853997,0.0008603752,0.0001831182],"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":[0.0001244458,0.00003277767,0.003513958,0.001785309,0.00007098488,0.00005270286,0.00005028175,0.0006559624,0.0003837765,0.001975429,0.9802514,0.01110299],"study_design_scores_gemma":[0.00007846714,0.00001134982,0.00282872,0.0003886596,0.00003067521,0.00006765858,0.00007679337,0.0004223423,0.0004105991,0.00232701,0.993335,0.0000227256],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001844527,0.0001744821,0.0001583158,0.0001354507,0.00004209987,0.00001148665,0.9973213,0.0003751061,0.001597182],"genre_scores_gemma":[0.0005020364,0.0001575531,0.0005976585,0.00009210858,0.000007442087,0.00004129936,0.9974931,0.00005759063,0.001051255],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06817497,"threshold_uncertainty_score":0.228068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01264566280224509,"score_gpt":0.3795903162710506,"score_spread":0.3669446534688055,"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."}}