{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00148633,0.0001835848,0.0003790539,0.0001841546,0.0003082581,0.00001772887,0.0002640534,0.00007167157,0.000707784],"category_scores_gemma":[0.002201953,0.0001398461,0.0002620555,0.0003844839,0.0002639556,0.00003439735,0.0001596129,0.0003674768,0.0000141974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002370323,"about_ca_system_score_gemma":0.0008277138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003513034,"about_ca_topic_score_gemma":0.00002012029,"domain_scores_codex":[0.9977478,0.0002600409,0.0005119569,0.0004149942,0.0006466919,0.0004184631],"domain_scores_gemma":[0.9936917,0.00550991,0.0001893219,0.0003163805,0.0001003062,0.0001923905],"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":[0.005953569,0.001668972,0.002356733,0.0005475385,0.0003892686,0.00009056577,0.0006255956,0.003278099,0.9754891,0.0000566897,0.0019344,0.007609518],"study_design_scores_gemma":[0.01858566,0.002694776,0.0006669278,0.00003908558,0.0002226325,0.00001306224,0.001198212,0.01372193,0.8203688,0.0001930001,0.142072,0.0002238659],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888785,0.001736469,0.0006976049,0.005449634,0.0003577366,0.002611556,0.0001050685,0.00004926086,0.000114115],"genre_scores_gemma":[0.9941284,0.002761707,0.000179061,0.0008997323,0.0001137838,0.0003201171,0.00001438084,0.00003435279,0.001548461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1551202,"threshold_uncertainty_score":0.7749738,"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."}}