{"id":"W2018585202","doi":"10.2174/1389200003339081","title":"Is it Possible to More Accurately Predict which Drug Candidates will cause Idiosyncratic Drug Reactions","year":2000,"lang":"en","type":"review","venue":"Current Drug Metabolism","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Drug; Drug reaction; Drug development; Drug discovery; Pharmacology; Medicine; Bioinformatics; Biology","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":[0.01130415,0.0009427511,0.002808903,0.001681099,0.0003729366,0.002914199,0.0007990234,0.003003122,0.0060097],"category_scores_gemma":[0.03731626,0.0007007289,0.002442067,0.00123149,0.001130282,0.004065629,0.0006059842,0.003121888,0.005687853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001104788,"about_ca_system_score_gemma":0.001043663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001501544,"about_ca_topic_score_gemma":0.001814499,"domain_scores_codex":[0.993799,0.002277304,0.0007939317,0.0008772725,0.001997927,0.0002545156],"domain_scores_gemma":[0.9526234,0.02416156,0.01308238,0.003146968,0.005950986,0.001034726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001815395,0.0006508096,0.2612978,0.002625691,0.001028619,0.001341033,0.0002077038,0.009715947,0.01288499,0.004736744,0.01877637,0.6849189],"study_design_scores_gemma":[0.0008460078,0.009607283,0.5287071,0.00332021,0.004645799,0.0160216,0.00137112,0.07688258,0.04931646,0.05264505,0.2559331,0.0007036578],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.3873173,0.1761065,0.2334832,0.120845,0.003981269,0.001794706,0.007252633,0.003310392,0.06590901],"genre_scores_gemma":[0.7528668,0.07526942,0.129899,0.02559084,0.003581487,0.0005881429,0.002879434,0.0003010298,0.009023817],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01130415,"threshold_uncertainty_score":0.0597828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09221617532129152,"score_gpt":0.4080121615469505,"score_spread":0.315795986225659,"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."}}