{"id":"W4220961149","doi":"10.1002/cti2.1380","title":"A scalable serology solution for profiling humoral immune responses to SARS‐CoV‐2 infection and vaccination","year":2022,"lang":"en","type":"article","venue":"Clinical & Translational Immunology","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Hospital; University of Alberta; University of Manitoba; University of Ottawa; Public Health Agency of Canada; Canadian Blood Services; Sunnybrook Health Science Centre; Health Sciences Centre; Institute of Infection and Immunity; National Research Council Canada; University of Toronto; Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute","funders":"Krembil Foundation; University of Toronto; National Research Council Canada; Canada Foundation for Innovation; Ontario Ministry of Research, Innovation and Science; Government of Ontario; Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Royal Bank of Canada; Public Health Agency of Canada","keywords":"Serology; Immunology; Immune system; Profiling (computer programming); Virology; Vaccination; Medicine; Antibody; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty); Computer science; Disease; Pathology","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":[0.00201866,0.00150621,0.001078983,0.00157019,0.0003581639,0.001251915,0.001302663,0.001424921,0.004536162],"category_scores_gemma":[0.002333328,0.0008177138,0.0008949874,0.0005099975,0.0003888942,0.0008264009,0.001295529,0.001457622,0.004120353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004247334,"about_ca_system_score_gemma":0.0006608636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004793872,"about_ca_topic_score_gemma":0.0007737616,"domain_scores_codex":[0.9974246,0.0003623105,0.000188334,0.0007188287,0.001133435,0.0001725467],"domain_scores_gemma":[0.9986176,0.0002841927,0.00022786,0.0002515027,0.0004701965,0.0001485395],"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":[0.0005661463,0.000365568,0.00706323,0.0005027697,0.0001732356,0.0001642572,0.0001095176,0.002568619,0.9072859,0.0007976005,0.008129739,0.07227355],"study_design_scores_gemma":[0.0001858216,0.001178048,0.01490031,0.0001910056,0.0001919193,0.0008058986,0.0001156858,0.05896956,0.8748628,0.00172907,0.0467103,0.0001595493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1194273,0.001858668,0.825537,0.001017094,0.0005775716,0.002453833,0.01169817,0.0317015,0.005728687],"genre_scores_gemma":[0.2604313,0.001239755,0.7089294,0.001188655,0.0003319171,0.004437516,0.01428813,0.00122403,0.007929401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004536162,"threshold_uncertainty_score":0.01517493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.127829313487605,"score_gpt":0.4525064659789341,"score_spread":0.3246771524913291,"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."}}