{"id":"W4252718118","doi":"10.1515/iupac.87.0601","title":"Serotoninergic","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; Neuroscience; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004948546,0.0008432512,0.0009338221,0.002328397,0.0004488101,0.001670232,0.001077401,0.001004889,0.05823525],"category_scores_gemma":[0.005014522,0.0003573801,0.001132061,0.00356672,0.0002109901,0.001064941,0.0009064777,0.001155581,0.03733186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009176998,"about_ca_system_score_gemma":0.001379099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01826012,"about_ca_topic_score_gemma":0.03861986,"domain_scores_codex":[0.9993698,0.0000776252,0.0001816888,0.0001802814,0.0001129455,0.00007769224],"domain_scores_gemma":[0.9978427,0.0006498047,0.0004759659,0.000355205,0.0005654793,0.0001108489],"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":[0.0006546814,0.00003696497,0.01431563,0.006161287,0.0001973014,0.0001517714,0.00006512145,0.000443946,0.0004204479,0.001194824,0.9501413,0.02621675],"study_design_scores_gemma":[0.0003521285,0.00006608108,0.0460414,0.002737991,0.0002551856,0.0005975388,0.0001371923,0.0004573761,0.0005980324,0.001906743,0.9467918,0.00005851701],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005955115,0.0005903841,0.00009472969,0.0001022811,0.00003443479,0.00001877735,0.9962718,0.0001148275,0.002177124],"genre_scores_gemma":[0.002682804,0.000752544,0.0004331261,0.0001998599,0.00002136467,0.000108248,0.9937189,0.00003511699,0.002048169],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9417648,"threshold_uncertainty_score":0.1948164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09395343089655644,"score_gpt":0.5042751457728716,"score_spread":0.4103217148763151,"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."}}