{"id":"W4248325672","doi":"10.1515/iupac.87.0040","title":"Aneurysm","year":2016,"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; Relation (database); Chemical nomenclature; Computer science; Psychology; Chemistry; Linguistics; Philosophy; Data mining; 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":[0.00112812,0.001320638,0.001178912,0.003070377,0.0008727953,0.003389234,0.002231397,0.001693016,0.2322831],"category_scores_gemma":[0.009732831,0.0005130732,0.001433219,0.005065052,0.0003265435,0.002540053,0.00202215,0.00157461,0.2534214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001509508,"about_ca_system_score_gemma":0.002648267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01493548,"about_ca_topic_score_gemma":0.02586011,"domain_scores_codex":[0.9982249,0.0002691336,0.000327862,0.0005907003,0.0003644115,0.0002230215],"domain_scores_gemma":[0.9959517,0.0009884281,0.0004581708,0.0008989862,0.001410069,0.0002926226],"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":[0.0001079946,0.00001331114,0.00122088,0.0007249836,0.00002041766,0.00002042078,0.00002170317,0.00009594297,0.00005845065,0.0008389627,0.9903369,0.006540085],"study_design_scores_gemma":[0.00009825779,0.00001261504,0.002404588,0.0004446755,0.00001867689,0.0000588096,0.00006981376,0.0001299,0.0001341519,0.001151765,0.9954612,0.00001562058],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001255047,0.0001133586,0.0001093615,0.0001327177,0.00005585643,0.00002858951,0.9955075,0.000390741,0.003536302],"genre_scores_gemma":[0.0005446363,0.0001464896,0.0004109826,0.0002331562,0.0000221998,0.0001079241,0.9954197,0.000110058,0.003004965],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2322831,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09796379738506794,"score_gpt":0.5052747634980084,"score_spread":0.4073109661129404,"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."}}