{"id":"W4303628983","doi":"10.3390/cells11193122","title":"Blood Endothelial-Cell Extracellular Vesicles as Potential Biomarkers for the Selection of Plasma in COVID-19 Convalescent Plasma Therapy","year":2022,"lang":"en","type":"article","venue":"Cells","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Héma-Québec; Université de Montréal; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Fondation Institut de Cardiologie de Montréal","keywords":"Endothelium; Inflammation; Medicine; Endothelial dysfunction; Cytokine storm; Immunology; Coronary artery disease; Endothelial stem cell; Disease; Endothelial activation; Extracellular; Blood plasma; Pathology; Internal medicine; Coronavirus disease 2019 (COVID-19); Biology; Cell biology; In vitro","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008441298,0.0002784735,0.0005599708,0.0005806476,0.0001566249,0.0007876719,0.0002242057,0.0004172068,0.0005641588],"category_scores_gemma":[0.0009840825,0.0001137866,0.0002281888,0.0003543771,0.0002008063,0.0003832423,0.0003393722,0.0005919233,0.0001750195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001871568,"about_ca_system_score_gemma":0.0001600326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002125985,"about_ca_topic_score_gemma":0.0002657791,"domain_scores_codex":[0.9994461,0.000234483,0.00004739182,0.0000754689,0.0001330958,0.00006344715],"domain_scores_gemma":[0.9996699,0.00007216643,0.0001143181,0.00002012585,0.00008856464,0.00003497484],"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":[0.002573099,0.0003469317,0.03279271,0.0007386486,0.0001330428,0.0004884507,0.000340604,0.0005691451,0.914396,0.0004486073,0.0005205638,0.04665215],"study_design_scores_gemma":[0.0001116662,0.00491832,0.167463,0.0002651708,0.0004657302,0.002582035,0.0008048203,0.00823768,0.797543,0.000873026,0.01665051,0.00008493492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9557337,0.0285267,0.01289572,0.0002908091,0.0001640215,0.0002121312,0.0006907663,0.00008807812,0.001398034],"genre_scores_gemma":[0.9878628,0.003376609,0.007196047,0.0001777302,0.00005877369,0.0001136314,0.0005676241,0.00001355381,0.0006331586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008441298,"threshold_uncertainty_score":0.004464269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03838325258625547,"score_gpt":0.3512751426560241,"score_spread":0.3128918900697686,"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."}}