{"id":"W2416731288","doi":"10.1503/cmaj.1150087","title":"NOACs: drug–drug interactions","year":2016,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Atrial Fibrillation Management and Outcomes","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rivaroxaban; Warfarin; Drug; Computer science; Medicine; Intensive care medicine; Pharmacology; Internal medicine; Atrial fibrillation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002433962,0.001152597,0.002461493,0.00102531,0.00212854,0.003545142,0.001488936,0.02010322,0.01358492],"category_scores_gemma":[0.02073608,0.0005084734,0.001390327,0.0009779983,0.002535554,0.005631424,0.001761212,0.02957224,0.01144976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002633522,"about_ca_system_score_gemma":0.002484137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001376037,"about_ca_topic_score_gemma":0.003815839,"domain_scores_codex":[0.9937845,0.00164039,0.0008818462,0.0007772349,0.002575484,0.0003403775],"domain_scores_gemma":[0.9846371,0.007850603,0.0021922,0.0004416754,0.003205028,0.001673505],"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":[0.00007088797,0.00007856812,0.002548363,0.0003257658,0.00005227918,0.01646774,0.0001574976,0.000145974,0.0004954466,0.004766324,0.9073856,0.06750567],"study_design_scores_gemma":[0.0001142774,0.0001447683,0.002301471,0.001504303,0.00007029188,0.07986307,0.0003466062,0.0007405492,0.0005946886,0.01845703,0.8957546,0.0001082091],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0008033318,0.01354833,0.0008292589,0.9569317,0.0176636,0.00003480974,0.00008221361,0.00007993495,0.01002671],"genre_scores_gemma":[0.0109736,0.01758701,0.001645466,0.7901952,0.1706806,0.00004334771,0.00008943612,0.00006633365,0.008718996],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02010322,"threshold_uncertainty_score":0.04544604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02196691951743911,"score_gpt":0.2936149922819499,"score_spread":0.2716480727645108,"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."}}