{"id":"W4253197492","doi":"10.1515/iupac.78.0148","title":"Antidote","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide and Herbicide Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Pesticide; Relation (database); Computer science; Management science; Chemistry; Ecology; Engineering; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001151976,0.001282059,0.001464391,0.003482395,0.0007197593,0.002531005,0.002255538,0.002152395,0.1632156],"category_scores_gemma":[0.01077017,0.0004581768,0.001692848,0.006162534,0.0003318286,0.002080784,0.001546714,0.001762532,0.09867118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001983329,"about_ca_system_score_gemma":0.0033886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01449161,"about_ca_topic_score_gemma":0.03321398,"domain_scores_codex":[0.9986124,0.0002794394,0.0002989152,0.0003613234,0.0003187013,0.0001292543],"domain_scores_gemma":[0.9956928,0.001745376,0.0007822991,0.000645362,0.0008718164,0.0002623151],"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":[0.0001860838,0.00001977312,0.000897922,0.003226726,0.00005814122,0.00002568149,0.00001629099,0.0002039712,0.00009018847,0.0008324116,0.9848676,0.009575222],"study_design_scores_gemma":[0.0002328226,0.00002408937,0.002251034,0.001239583,0.00006878777,0.00007243146,0.00003092499,0.0001265915,0.0001465602,0.001412896,0.9943755,0.00001879047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001087259,0.0005503588,0.00008524241,0.0002233442,0.0000429094,0.00002872226,0.9963778,0.0001591622,0.002423697],"genre_scores_gemma":[0.0009101398,0.000824424,0.000510292,0.0006569388,0.00003181745,0.0002211853,0.9943017,0.00009369826,0.002449906],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8367844,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01064465149959216,"score_gpt":0.3532548455480727,"score_spread":0.3426101940484806,"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."}}