{"id":"W1842977100","doi":"10.1002/9780470921920.edm119","title":"Current and Future Tools for Predicting Clinical Drug–Drug Interactions","year":2012,"lang":"en","type":"other","venue":"Encyclopedia of Drug Metabolism and Interactions","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Intertek (Canada)","funders":"","keywords":"Drug; Computer science; Drug development; Field (mathematics); Data science; Risk analysis (engineering); Computational biology; Medicine; Pharmacology; Biology; Mathematics","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":[0.004906306,0.001830526,0.001491425,0.005776042,0.0002739154,0.003717035,0.001348467,0.0008302713,0.01809716],"category_scores_gemma":[0.01101907,0.0004628193,0.00105575,0.003296976,0.0004906551,0.001761314,0.001126731,0.001321233,0.01092884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006964858,"about_ca_system_score_gemma":0.00118351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001825301,"about_ca_topic_score_gemma":0.001610582,"domain_scores_codex":[0.9971539,0.001124837,0.000271632,0.0003547372,0.001008115,0.00008676245],"domain_scores_gemma":[0.994186,0.003123787,0.000646555,0.0005170495,0.001350014,0.0001765314],"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":[0.0003278956,0.0002406216,0.01909848,0.001599316,0.0003557944,0.0001785229,0.00005263762,0.006701214,0.004465747,0.009433609,0.02512632,0.9324199],"study_design_scores_gemma":[0.0003037397,0.001061104,0.0467678,0.003355545,0.001624098,0.004774774,0.0004160884,0.2387825,0.03663198,0.09294617,0.572938,0.0003981985],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02930018,0.1952499,0.6286218,0.01123801,0.001625509,0.001173924,0.02572454,0.01952297,0.08754317],"genre_scores_gemma":[0.221897,0.1220689,0.6030661,0.002446583,0.001759766,0.0009480644,0.0234211,0.0007602127,0.02363228],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01809716,"threshold_uncertainty_score":0.06054103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07688309488247434,"score_gpt":0.4458639384986488,"score_spread":0.3689808436161744,"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."}}