{"id":"W4249468208","doi":"10.1515/iupac.78.0363","title":"Identification","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide Residue Analysis and Safety","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Identification (biology); Relation (database); Computer science; Chemical nomenclature; Data science; Management science; Ecology; Engineering; Chemistry; Biology; Data mining; 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":[0.001937578,0.001888306,0.001782064,0.009088751,0.001273612,0.003647683,0.002962865,0.002560427,0.1402607],"category_scores_gemma":[0.01608564,0.0007013502,0.001583652,0.01314578,0.0006572733,0.004066384,0.002628991,0.00270067,0.1441832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002787933,"about_ca_system_score_gemma":0.005768916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02147088,"about_ca_topic_score_gemma":0.03539626,"domain_scores_codex":[0.9966655,0.0004646992,0.0008085414,0.001075559,0.0006697222,0.0003159467],"domain_scores_gemma":[0.9932547,0.002102883,0.0008065409,0.001301154,0.002146305,0.000388306],"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":[0.00006316158,0.00001547643,0.00089353,0.00158515,0.00002592062,0.00003653595,0.00004081738,0.000153734,0.000145717,0.001222117,0.9910764,0.004741573],"study_design_scores_gemma":[0.00007342882,0.000008559794,0.001726029,0.000696316,0.00001893908,0.00005938967,0.00008960622,0.0001256989,0.0001353092,0.001348821,0.9956985,0.00001936666],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006802689,0.0001219107,0.0001057662,0.00007559008,0.00002523802,0.0000316445,0.9984061,0.0001190856,0.001046619],"genre_scores_gemma":[0.0002146978,0.0001316018,0.0004167165,0.0001052251,0.000008700602,0.0002299046,0.9979808,0.00004903655,0.0008633981],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1402607,"threshold_uncertainty_score":0.4692189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01515193683869891,"score_gpt":0.3585784617477983,"score_spread":0.3434265249090994,"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."}}