{"id":"W3132386419","doi":"10.1111/trf.16318","title":"High‐throughput detection of antibodies targeting the <scp>SARS‐CoV</scp> ‐2 <scp>Spike</scp> in longitudinal convalescent plasma samples","year":2021,"lang":"en","type":"article","venue":"Transfusion","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Héma-Québec; Université de Montréal; McGill University; Centre Hospitalier de l’Université de Montréal","funders":"U.S. Military HIV Research Program; Servier","keywords":"Antibody; Virology; Convalescent plasma; Immunology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Flow cytometry; Coronavirus; Glycoprotein; Biology; Spike (software development); Coronavirus disease 2019 (COVID-19); Virus; Medicine; Disease; Internal medicine; Infectious disease (medical specialty); Genetics","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":[0.0007037715,0.0003541349,0.0003003591,0.000482025,0.0002868019,0.0004190878,0.0002809005,0.0004467659,0.0006556885],"category_scores_gemma":[0.0004922729,0.0001640939,0.0002657056,0.0003786433,0.0002119953,0.0001863208,0.0002362725,0.0006017699,0.000327783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002931274,"about_ca_system_score_gemma":0.0002501333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001057859,"about_ca_topic_score_gemma":0.00116191,"domain_scores_codex":[0.9995674,0.00005654653,0.00002595469,0.000133361,0.0001582635,0.00005846203],"domain_scores_gemma":[0.999635,0.00008085444,0.00005855141,0.00002974962,0.0001530129,0.00004285425],"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":[0.000246549,0.0001717141,0.01728555,0.0000618481,0.00003437028,0.00006924458,0.0001024807,0.0002714683,0.9771622,0.00004940685,0.0003420914,0.004203112],"study_design_scores_gemma":[0.00006429296,0.002108054,0.195829,0.00002511623,0.0001163224,0.001230703,0.0002445065,0.0103228,0.786023,0.0002019751,0.003796966,0.0000373067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823095,0.0005119269,0.01408483,0.0001005674,0.0000287497,0.0001665874,0.001664503,0.0002575407,0.0008758464],"genre_scores_gemma":[0.9770935,0.0003748311,0.01649355,0.0002439029,0.00003714263,0.0002893759,0.004251494,0.00002608587,0.001190136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001057859,"threshold_uncertainty_score":0.003721893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04737162282876464,"score_gpt":0.3175960510745088,"score_spread":0.2702244282457442,"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."}}