{"id":"W2058114494","doi":"10.1136/ebm.11.4.120","title":"The Outpatient Bleeding Risk Index predicted major bleeding in patients taking warfarin","year":2006,"lang":"en","type":"letter","venue":"Evidence-Based Medicine","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Warfarin; Medicine; Index (typography); Major bleeding; Internal medicine; Atrial fibrillation; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003888021,0.0003377184,0.0003449177,0.0005849411,0.0002006296,0.0005680689,0.0002885049,0.0005658514,0.004736508],"category_scores_gemma":[0.004273034,0.000184858,0.000530235,0.0006207168,0.0001023672,0.0004187224,0.0002779459,0.0009308241,0.0006899445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001911344,"about_ca_system_score_gemma":0.0002597027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004204314,"about_ca_topic_score_gemma":0.004202116,"domain_scores_codex":[0.9998398,0.00004490593,0.00002647323,0.0000279089,0.0000361908,0.00002467659],"domain_scores_gemma":[0.998741,0.0004015598,0.0004382122,0.00005802792,0.0001394271,0.000221753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004603218,0.00004845509,0.9954904,0.00001032085,0.00003486041,0.00004297471,0.00001550778,0.00005448119,0.0001087579,0.00002614373,0.001574341,0.002133487],"study_design_scores_gemma":[0.0000975822,0.0002765416,0.9967278,0.00002430498,0.0001032703,0.0003151852,0.00006983209,0.001731834,0.00006092083,0.00008221235,0.0005021339,0.000008381669],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931586,0.0006266368,0.000232527,0.0006550999,0.00009225482,0.00002652939,0.00167131,0.00003093455,0.003506146],"genre_scores_gemma":[0.9970434,0.0001822622,0.0002943051,0.0001589573,0.0001314766,0.00001700698,0.001469548,0.000009798696,0.000693349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004736508,"threshold_uncertainty_score":0.01584524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03251692797558094,"score_gpt":0.2763812668950657,"score_spread":0.2438643389194848,"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."}}