{"id":"W2588139273","doi":"10.1182/blood.v120.21.1091.1091","title":"An in-Vitro Model Using Thromboelastography to Evaluate the Effects of Anticoagulants On Clot Formation in Plasma Enriched with Autologous Platelets","year":2012,"lang":"en","type":"article","venue":"Blood","topic":"Platelet Disorders and Treatments","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Thrombosis and Atherosclerosis Research Institute; McMaster University Medical Centre","funders":"","keywords":"Thromboelastography; Platelet; Fondaparinux; Antithrombotic; Rivaroxaban; Platelet-poor plasma; Dabigatran; Tissue factor; Chemistry; Clotting time; Thrombelastography; Recombinant factor VIIa; Pharmacology; Anticoagulant; Platelet-rich plasma; Thromboplastin; Heparin; Medicine; Thrombosis; Anesthesia; Coagulation; Internal medicine; Warfarin; Biochemistry","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":[0.000640988,0.0006417496,0.0005618824,0.0003018001,0.0002122232,0.0005559747,0.0004582934,0.0005367466,0.001314745],"category_scores_gemma":[0.0003034417,0.0002291403,0.0006087091,0.0004444091,0.0002301571,0.000289376,0.0003068217,0.0008477062,0.0004943935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002713781,"about_ca_system_score_gemma":0.0002681436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006110886,"about_ca_topic_score_gemma":0.0005507998,"domain_scores_codex":[0.9992778,0.0002195007,0.0000936808,0.0001347985,0.0001913662,0.00008295442],"domain_scores_gemma":[0.9995753,0.0001726857,0.00007979712,0.00008222547,0.000060213,0.00002978106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003668735,0.0002839916,0.0003156544,0.0001754676,0.00002778748,0.0002059493,0.00005836469,0.0004094788,0.9964748,0.0001413658,0.000096465,0.001443826],"study_design_scores_gemma":[0.00007435603,0.002759843,0.002743378,0.00002168263,0.0001069707,0.0005999707,0.00004413965,0.006863133,0.9844481,0.0001256561,0.002196191,0.00001652291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9438719,0.008330854,0.0410542,0.000252228,0.000259839,0.0004146505,0.001146431,0.0001698106,0.004500133],"genre_scores_gemma":[0.969858,0.003341021,0.02256836,0.0001627555,0.00007415252,0.0003566156,0.001536208,0.00002941174,0.002073539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001314745,"threshold_uncertainty_score":0.004398286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02116357318786661,"score_gpt":0.2882661198550872,"score_spread":0.2671025466672206,"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."}}