{"id":"W2137827821","doi":"10.1002/0471250953.bi1404s18","title":"In Silico Drug Exploration and Discovery Using DrugBank","year":2007,"lang":"en","type":"article","venue":"Current Protocols in Bioinformatics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Genome Alberta","keywords":"DrugBank; In silico; Drug discovery; Computational biology; Drug; Computer science; Pharmacology; Medicine; Bioinformatics; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001927606,0.0001769945,0.0002049783,0.0004652477,0.00005914808,0.0003542547,0.0004347604,0.00004593347,0.000001199386],"category_scores_gemma":[0.0001331758,0.0001715411,0.00003432352,0.0008429958,0.00005938641,0.006935509,0.0003775606,0.0002455407,0.000006239275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000187548,"about_ca_system_score_gemma":0.0001459696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001020352,"about_ca_topic_score_gemma":0.00002723957,"domain_scores_codex":[0.9981746,0.00009338342,0.0007995647,0.0002218596,0.0003714311,0.0003391806],"domain_scores_gemma":[0.9990591,0.0002833463,0.000214427,0.0003245016,0.00004918873,0.00006940986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001090578,0.0008160543,0.01960244,0.001699833,0.00001136915,0.000025975,0.03070056,0.0819821,0.000222175,0.2083693,0.0003603812,0.6561007],"study_design_scores_gemma":[0.000811218,0.00002661885,0.003877341,0.0004274947,0.00000130074,0.000008966837,0.0002342193,0.9635192,0.001146151,0.02791373,0.00176089,0.0002729191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04988009,0.0000441876,0.9320982,0.0001500708,0.0002913042,0.01722454,0.00000261846,0.00004022874,0.0002687509],"genre_scores_gemma":[0.1266095,0.00004186801,0.8580778,0.0003846884,0.0002434772,0.01454588,0.00002086852,0.0000353889,0.00004059986],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.881537,"threshold_uncertainty_score":0.6995243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07871889536768117,"score_gpt":0.4056771312917395,"score_spread":0.3269582359240584,"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."}}