{"id":"W4256018727","doi":"10.1515/iupac.79.1598","title":"Medicine","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 Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001098554,0.001193923,0.001369473,0.003130447,0.0008052883,0.002996029,0.002019562,0.001679922,0.2416123],"category_scores_gemma":[0.01361494,0.0004056508,0.001620366,0.006283959,0.0002761292,0.002072883,0.001803567,0.001433361,0.1927908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001734275,"about_ca_system_score_gemma":0.003200052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01714812,"about_ca_topic_score_gemma":0.0281599,"domain_scores_codex":[0.9983419,0.0003139623,0.0003403994,0.0005239529,0.0003018529,0.0001780268],"domain_scores_gemma":[0.9951534,0.001410082,0.0007270036,0.0009342151,0.001419844,0.0003553801],"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":[0.0001353505,0.0000174064,0.001869041,0.001618937,0.00005812179,0.00002287951,0.00002368415,0.0001372912,0.0000511644,0.0009282062,0.9776952,0.01744282],"study_design_scores_gemma":[0.0001594061,0.00002059325,0.005544168,0.001353348,0.00006010655,0.00009602546,0.00007643109,0.0001529821,0.00009778221,0.002025137,0.9903908,0.00002338614],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001591696,0.0004366139,0.000130265,0.0002612175,0.00007154883,0.00003580341,0.9945441,0.0001696384,0.00419148],"genre_scores_gemma":[0.001067542,0.0006435199,0.000538801,0.0006111631,0.00005819722,0.0002026071,0.9929069,0.00006991516,0.003901229],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7583877,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02084172907239067,"score_gpt":0.4476741727238983,"score_spread":0.4268324436515076,"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."}}