{"id":"W4293392998","doi":"10.1016/j.heliyon.2022.e10270","title":"Comparative performance data for multiplex SARS-CoV-2 serological assays from a large panel of dried blood spot specimens","year":2022,"lang":"en","type":"article","venue":"Heliyon","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; National Research Council Canada; University of Toronto; Institute of Infection and Immunity; University of Ottawa; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; University of Manitoba; Public Health Agency of Canada","funders":"Canada Foundation for Innovation; Government of Ontario; Ontario Genomics; Genome Canada","keywords":"Dried blood spot; Multiplex; Medicine; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Serology; Virology; Dried blood; Antibody titer; Pandemic; Antibody; Immunoassay; Titer; 2019-20 coronavirus outbreak; Immunology; Biology; Disease; Internal medicine; Infectious disease (medical specialty); Bioinformatics","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":[0.000670432,0.0002118506,0.0006288577,0.0001275707,0.0002213321,0.00001690088,0.0006029813,0.0001015747,0.0001337794],"category_scores_gemma":[0.0001866432,0.000186401,0.0001131849,0.0002961996,0.0001101126,0.000112335,0.0007732119,0.0004965326,0.00006876453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007380592,"about_ca_system_score_gemma":0.0002022896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006533715,"about_ca_topic_score_gemma":0.00008051796,"domain_scores_codex":[0.997635,0.0001425904,0.0004107996,0.0006241646,0.0006672785,0.0005201572],"domain_scores_gemma":[0.9982405,0.0004134939,0.0001381945,0.001026395,0.0001426845,0.00003874295],"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":[0.002869328,0.001565671,0.07331631,0.0003187858,0.0002742269,0.0000622743,0.001027989,0.000002673181,0.9181807,0.0001241082,0.002084831,0.0001731288],"study_design_scores_gemma":[0.00920024,0.001914977,0.03743455,0.0001049094,0.0002103773,0.00003434416,0.0008809071,0.01390953,0.7264319,0.00005248326,0.2095531,0.0002726628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943132,0.0007497961,0.0002357813,0.0002063604,0.0001288906,0.001010833,0.00196296,0.00006777342,0.001324361],"genre_scores_gemma":[0.9886765,0.00002804269,0.001156091,0.009115653,0.0002207517,0.0001659833,0.0005493569,0.0000278367,0.00005972511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2074683,"threshold_uncertainty_score":0.7601213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2261551830898515,"score_gpt":0.3951593008316353,"score_spread":0.1690041177417838,"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."}}