{"id":"W4406378262","doi":"10.1111/trf.18124","title":"Freeze‐dried plasma: Hemostasis and biophysical analyses for damage control resuscitation","year":2025,"lang":"en","type":"article","venue":"Transfusion","topic":"Trauma, Hemostasis, Coagulopathy, Resuscitation","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; McMaster University; Thrombosis and Atherosclerosis Research Institute; Hamilton Health Sciences; University of Toronto; Defence Research and Development Canada; Canadian Blood Services; St. Michael's Hospital","funders":"Canadian Institutes of Health Research; National Institutes of Health; Defence Research and Development Canada; Hospital for Sick Children; York University; Canadian Blood Services; McMaster University; National Heart, Lung, and Blood Institute; Heart and Stroke Foundation of Canada","keywords":"Resuscitation; Hemostasis; Fresh frozen plasma; Whole blood; Coagulation; Chemistry; Medicine; Hemorrhagic shock; Platelet; Anesthesia; Surgery; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002434379,0.0002089116,0.0004158329,0.0002996619,0.0002156758,0.00004069299,0.00007113864,0.0001504734,0.00001794183],"category_scores_gemma":[0.0002471709,0.0001916074,0.0001491013,0.0005073687,0.0001199094,0.0001501699,0.00001114671,0.0001597604,0.00000602617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007253715,"about_ca_system_score_gemma":0.00009885135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001032709,"about_ca_topic_score_gemma":0.0001776142,"domain_scores_codex":[0.9985622,0.00007215438,0.0003742894,0.0004547085,0.0002703449,0.0002663684],"domain_scores_gemma":[0.9988403,0.0004762232,0.00006347995,0.0002777016,0.0002234303,0.0001189049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003895477,0.0003191492,0.005064304,0.0005250007,0.0001929843,0.00001315695,0.0008277413,0.00004937583,0.8860358,0.00204821,0.001341159,0.09968761],"study_design_scores_gemma":[0.03227523,0.001365088,0.4701055,0.0006587746,0.002115634,0.000009974151,0.001561217,0.02531258,0.4592958,0.002853111,0.00392412,0.0005229855],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952574,0.0001663242,0.03902726,0.005026839,0.0002315735,0.001413719,0.0001055453,0.0001404664,0.00131425],"genre_scores_gemma":[0.9948792,0.0001477147,0.003847714,0.0004705894,0.00008717377,0.0001008528,0.0001598559,0.00002555269,0.0002813572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4650412,"threshold_uncertainty_score":0.7813524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0370330555344259,"score_gpt":0.3504130832083238,"score_spread":0.3133800276738978,"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."}}