{"id":"W2024038403","doi":"10.1093/nar/gku1068","title":"BRENDA in 2015: exciting developments in its 25th year of existence","year":2014,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":195,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Bundesministerium für Bildung und Forschung","keywords":"Annotation; Information retrieval; Relevance (law); Computer science; KEGG; Computational biology; Function (biology); Ontology; Biology; Data mining; Artificial intelligence; Gene ontology; Biochemistry; Genetics; Gene","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":[0.01734525,0.002337191,0.00207909,0.004446201,0.001632899,0.0109265,0.003732181,0.003662009,0.07188483],"category_scores_gemma":[0.01375367,0.0008790424,0.001466599,0.003742904,0.001935256,0.008882305,0.009613859,0.004986664,0.08275592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003705622,"about_ca_system_score_gemma":0.007348139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003861388,"about_ca_topic_score_gemma":0.003399325,"domain_scores_codex":[0.9954573,0.0007162208,0.0003452442,0.0007995085,0.001957937,0.0007238345],"domain_scores_gemma":[0.9808953,0.001838001,0.000688002,0.001441939,0.004279888,0.01085679],"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":[0.0002988816,0.00008134651,0.0007471588,0.0004327169,0.00002439199,0.0002066369,0.0002355658,0.000211025,0.00146816,0.01261626,0.7281356,0.2555423],"study_design_scores_gemma":[0.000006797343,0.00002702246,0.0002288803,0.00009153881,0.000003228228,0.00007450183,0.00003343505,0.00005645473,0.0003150966,0.0009119816,0.9982359,0.00001510794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.006843416,0.2661633,0.08694007,0.1178849,0.2792604,0.0003583991,0.01404787,0.03119079,0.1973108],"genre_scores_gemma":[0.03235179,0.1279737,0.08033311,0.02525291,0.0487703,0.0004986406,0.03330369,0.01623916,0.6352766],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07188483,"threshold_uncertainty_score":0.2404787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06924922146140024,"score_gpt":0.3853085447481472,"score_spread":0.316059323286747,"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."}}