{"id":"W4233177141","doi":"10.1515/iupac.79.2136","title":"Toxic","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Immunotoxicology and immune responses","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Organic chemistry","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":[0.001254083,0.002090525,0.001713261,0.004022419,0.0008908614,0.003189653,0.002951145,0.001834912,0.104514],"category_scores_gemma":[0.008005697,0.0006481441,0.002163117,0.005950655,0.0003591616,0.002110019,0.002103472,0.001933687,0.115551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001934525,"about_ca_system_score_gemma":0.003501739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02079343,"about_ca_topic_score_gemma":0.04160544,"domain_scores_codex":[0.9983073,0.0002699319,0.0002944961,0.0005396602,0.0004198707,0.0001686308],"domain_scores_gemma":[0.9970827,0.0007819107,0.0004195969,0.0006492445,0.0008466343,0.0002199727],"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":[0.0001474148,0.00002368586,0.00190745,0.002677609,0.00008175663,0.00003552581,0.00002753767,0.0004160911,0.0001750392,0.001149098,0.9849554,0.008403336],"study_design_scores_gemma":[0.0001456198,0.00001498834,0.002999425,0.0006557782,0.00005683853,0.00006267581,0.00003886237,0.0002034001,0.000184551,0.001242952,0.9943742,0.00002080901],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009233142,0.000199311,0.00008632959,0.00006537595,0.00002765967,0.0000146132,0.9979773,0.0002396348,0.001297356],"genre_scores_gemma":[0.0003083253,0.0001851839,0.0003083641,0.0001160933,0.00000915891,0.00006295485,0.9979489,0.00006552077,0.0009955001],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.104514,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151633348401497,"score_gpt":0.3702067318254179,"score_spread":0.3586903983414029,"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."}}