{"id":"W2996098367","doi":"10.1093/ehjcvp/pvz076","title":"New artificial intelligence prediction model using serial prothrombin time international normalized ratio measurements in atrial fibrillation patients on vitamin K antagonists: GARFIELD-AF","year":2019,"lang":"en","type":"article","venue":"European Heart Journal - Cardiovascular Pharmacotherapy","topic":"Atrial Fibrillation Management and Outcomes","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Nakatani Foundation for Advancement of Measuring Technologies in Biomedical Engineering; Ministry of Education, Culture, Sports, Science and Technology; Vehicle Racing Commemorative Foundation; Bayer; Bristol-Myers Squibb","keywords":"Atrial fibrillation; Internal medicine; Vitamin k; Cardiology; Medicine; Prothrombin time; Vitamin K antagonist; Warfarin","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":[0.001451185,0.0009342195,0.000715766,0.000932457,0.0003706024,0.001079012,0.0007929886,0.0008190431,0.001372378],"category_scores_gemma":[0.003469162,0.0002711823,0.0008232787,0.0004916888,0.0002371864,0.0005423142,0.0005063156,0.001074599,0.0002850227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031707,"about_ca_system_score_gemma":0.0009585817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01687794,"about_ca_topic_score_gemma":0.008296207,"domain_scores_codex":[0.9996102,0.0001090764,0.00003477194,0.0001259165,0.00006606559,0.00005401478],"domain_scores_gemma":[0.9987265,0.0007841082,0.0001233349,0.00003365968,0.0002854834,0.00004677125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004724704,0.0003777981,0.04608072,0.0000680587,0.0003360675,0.0002824112,0.0001148005,0.8757033,0.001124753,0.0007530973,0.002120085,0.07256654],"study_design_scores_gemma":[0.000009147182,0.00003842867,0.001424633,0.000005377059,0.0000199372,0.00001605601,0.000005192286,0.9980358,0.00009892239,0.0002803821,0.00006239725,0.00000360843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7636414,0.001130305,0.2253806,0.002171773,0.0002526503,0.0002219846,0.001207146,0.00127608,0.004718004],"genre_scores_gemma":[0.979914,0.0002129404,0.01682137,0.0001831111,0.00005337967,0.000151414,0.0006752081,0.00001463736,0.001973961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01687794,"threshold_uncertainty_score":0.03355944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1088366436884087,"score_gpt":0.3503914368703736,"score_spread":0.2415547931819649,"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."}}