{"id":"W2170146596","doi":"10.1093/nar/gkj067","title":"DrugBank: a comprehensive resource for in silico drug discovery and exploration","year":2005,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":4028,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"DrugBank; PubChem; Cheminformatics; In silico; chEMBL; Protein Data Bank; Drug discovery; Bioinformatics; Drug; Computational biology; Biology; Computer science; Database; Pharmacology; Protein structure; Genetics","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":[0.00521434,0.002461612,0.00342415,0.006493036,0.00107033,0.003435125,0.004691988,0.001497967,0.04686037],"category_scores_gemma":[0.009276511,0.00164728,0.001418075,0.006570997,0.0006031547,0.003149998,0.003490494,0.002464495,0.03325843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215606,"about_ca_system_score_gemma":0.005118042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003792007,"about_ca_topic_score_gemma":0.004595105,"domain_scores_codex":[0.9980147,0.0006867792,0.0002527218,0.0002793023,0.0006412466,0.0001252336],"domain_scores_gemma":[0.9959991,0.00211338,0.0003341593,0.0006564046,0.0004361141,0.0004609044],"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":[0.0006480984,0.0002259142,0.001294362,0.003068981,0.0002791741,0.0003096202,0.0001040014,0.009131902,0.003705282,0.0127145,0.8678097,0.1007086],"study_design_scores_gemma":[0.0008722513,0.0001750042,0.00157833,0.0004870612,0.0002367406,0.0005733105,0.00005808045,0.02481018,0.006505422,0.02078689,0.9437788,0.0001379569],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.006742178,0.01313371,0.1886028,0.0028162,0.0005684919,0.001591649,0.5444041,0.198445,0.04369594],"genre_scores_gemma":[0.02021343,0.009606679,0.2403471,0.001027705,0.0001859095,0.002395982,0.7059345,0.01107673,0.009212047],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04686037,"threshold_uncertainty_score":0.1567636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08993724777240726,"score_gpt":0.3895307683833659,"score_spread":0.2995935206109586,"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."}}