{"id":"W2883553853","doi":"10.1016/j.transci.2018.07.004","title":"Bleeding by the numbers: The utility and the limitations of bleeding scores, bleeding prediction tools, and bleeding case definitions","year":2018,"lang":"en","type":"review","venue":"Transfusion and Apheresis Science","topic":"Antiplatelet Therapy and Cardiovascular Diseases","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Medicine; Antithrombotic; Major bleeding; Bleeding time; Von Willebrand disease; Stroke (engine); Intensive care medicine; Von Willebrand factor; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.002960015,0.0003578095,0.0008469076,0.0001296598,0.002676885,0.0003267373,0.0002803416,0.0001604797,0.00004900492],"category_scores_gemma":[0.0003887857,0.0001718232,0.0003958064,0.001022307,0.004168872,0.0003969486,0.0001161266,0.000443043,0.000001359494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003198128,"about_ca_system_score_gemma":0.00020476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000167818,"about_ca_topic_score_gemma":0.00005073861,"domain_scores_codex":[0.9975276,0.000224926,0.0005936844,0.0006320225,0.0006517145,0.0003700365],"domain_scores_gemma":[0.9975808,0.00139037,0.0002246234,0.0004183042,0.0001884261,0.0001974545],"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":[0.0001570353,0.0000835903,0.0002198093,0.002648656,0.0005510641,0.00002919485,0.002701993,5.615539e-7,0.0001909464,0.00304278,0.0007973915,0.989577],"study_design_scores_gemma":[0.01172009,0.0009171097,0.001882617,0.04643072,0.03718673,0.02616626,0.05501678,0.003907753,0.000423433,0.001896628,0.8124496,0.002002307],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02994893,0.9641058,0.0003287618,0.0005142109,0.0001976754,0.00147382,0.0002381033,0.00005146204,0.00314122],"genre_scores_gemma":[0.1379977,0.8615472,0.00008297272,0.00008254039,0.0001420144,0.00007159841,0.00001609118,0.00002146279,0.00003837468],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9875747,"threshold_uncertainty_score":0.9986215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1391298683522,"score_gpt":0.3088326079992385,"score_spread":0.1697027396470386,"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."}}