{"id":"W2888872909","doi":"10.1111/trf.14782","title":"Screening of red blood cells for extracellular vesicle content as a product quality indicator","year":2018,"lang":"en","type":"article","venue":"Transfusion","topic":"Blood transfusion and management","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Lions Gate Hospital; Canadian Blood Services; University of Alberta","funders":"Canadian Blood Services","keywords":"Hemolysis; Red blood cell; Filtration (mathematics); Extracellular vesicles; Biomedical engineering; Chemistry; Hemoglobin; Extracellular vesicle; Chromatography; Medicine; Biochemistry; Biology; Cell biology; Immunology; Mathematics","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":[0.0006946573,0.0001662417,0.0003828512,0.0001229026,0.000118603,0.000008150326,0.0001115884,0.00008160246,0.0004555479],"category_scores_gemma":[0.00003652868,0.0001424706,0.0001991019,0.0001837133,0.0001323235,0.00005745127,0.00001754941,0.0001169353,0.00001925101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001218481,"about_ca_system_score_gemma":0.00004877275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003131904,"about_ca_topic_score_gemma":0.0000421817,"domain_scores_codex":[0.9983702,0.00005896978,0.0005116785,0.0004184022,0.0003744604,0.0002662582],"domain_scores_gemma":[0.9991212,0.00004151218,0.0001069617,0.0004276211,0.000145806,0.0001569198],"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":[0.001538499,0.0009187072,0.001077845,0.0004227155,0.0001459189,0.000007323981,0.0007875988,3.881924e-7,0.9776816,0.0009841942,0.0003557816,0.0160794],"study_design_scores_gemma":[0.007270839,0.001608252,0.01223529,0.0001806282,0.0005136934,0.000008635396,0.0004137968,0.00004088197,0.9632614,0.00006198548,0.01424481,0.0001597349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770268,0.0003333704,0.01593205,0.002385254,0.000206169,0.002350865,0.00001665488,0.00009749232,0.001651399],"genre_scores_gemma":[0.9892356,0.0002015137,0.008432647,0.0003655003,0.0001770903,0.00006039674,0.00002069973,0.00003172542,0.001474832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01591967,"threshold_uncertainty_score":0.5809784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0633854115459203,"score_gpt":0.3077202040713278,"score_spread":0.2443347925254075,"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."}}