{"id":"W4247161733","doi":"10.1515/iupac.88.1484","title":"Vertebra","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; 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":[],"consensus_categories":[],"category_scores_codex":[0.000922355,0.001406832,0.001380881,0.00524978,0.001045965,0.003830092,0.002321299,0.001674617,0.2563347],"category_scores_gemma":[0.009374019,0.0006348203,0.001603421,0.008067595,0.0004287414,0.002902122,0.00258259,0.001798262,0.2953019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001749006,"about_ca_system_score_gemma":0.002868399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02140895,"about_ca_topic_score_gemma":0.03929862,"domain_scores_codex":[0.9983763,0.0002374129,0.0003370223,0.0005138994,0.0003461536,0.0001893066],"domain_scores_gemma":[0.9961581,0.001042979,0.0004668106,0.0007954161,0.001283602,0.0002531757],"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":[0.00006766405,0.00001007336,0.0008279039,0.00137225,0.00002584074,0.00001867038,0.00003047468,0.0001130891,0.00008830713,0.001112158,0.9890102,0.007323531],"study_design_scores_gemma":[0.00004435133,0.000006847328,0.001599077,0.0005264588,0.000014037,0.00003386796,0.00004910724,0.000072347,0.00008270446,0.0009590802,0.9966003,0.00001173489],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007533547,0.0001529244,0.00009916828,0.00009538876,0.00005067479,0.00001743206,0.9960401,0.0003403659,0.003128603],"genre_scores_gemma":[0.0003418256,0.0002161193,0.0004102236,0.000150822,0.00001884071,0.00008269273,0.9958871,0.0001466814,0.002745791],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2563347,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1257491887687765,"score_gpt":0.5369415219607597,"score_spread":0.4111923331919832,"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."}}