{"id":"W4251621304","doi":"10.1515/iupac.87.0336","title":"Kainic Acid","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; Chemical nomenclature; Relation (database); Computer science; Psychology; Chemistry; Linguistics; Philosophy; Organic chemistry; 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":[0.0006961232,0.001181317,0.001215099,0.003630803,0.0006263133,0.002352545,0.001682439,0.001292277,0.07723314],"category_scores_gemma":[0.006472597,0.0004758194,0.001257015,0.005655468,0.0002862612,0.001603706,0.001414926,0.001441587,0.08350842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001209813,"about_ca_system_score_gemma":0.002271696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01328708,"about_ca_topic_score_gemma":0.02730862,"domain_scores_codex":[0.9990579,0.000129866,0.0002757103,0.0002512065,0.0001949798,0.0000903569],"domain_scores_gemma":[0.9976168,0.0006697783,0.0004862999,0.0004631137,0.000611488,0.0001525527],"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":[0.000424406,0.00003777228,0.002579452,0.005583454,0.0001060807,0.00006324164,0.0000438393,0.0004191102,0.0004594387,0.001140974,0.9732588,0.01588338],"study_design_scores_gemma":[0.0002305626,0.0000287328,0.005625595,0.000882016,0.00006786737,0.0001252933,0.00005451461,0.0001829053,0.0003664405,0.001196253,0.9912094,0.00003052189],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002231594,0.0003578692,0.00007936091,0.0000661061,0.00002687231,0.00002219782,0.9975225,0.0001944703,0.00150753],"genre_scores_gemma":[0.0007310112,0.0004229715,0.0003560442,0.0001044919,0.000008472787,0.00008738155,0.9970071,0.00004835222,0.001234154],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07723314,"threshold_uncertainty_score":0.2583706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1061497864984377,"score_gpt":0.5121859203992433,"score_spread":0.4060361339008056,"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."}}