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Canadian society of clinical chemists (CSCC) interim consensus guidance for testing and reporting of SARS-CoV-2 serology

2020· review· en· W3091637530 on OpenAlexaffabout
Dana Bailey, Danijela Konforte, Vilte Barakauskas, Paul S. F. Yip, Vathany Kulasingam, Mohamed Abou El Hassan, Lori Beach, Ivan M. Blasutig, Peter Catomeris, Kent Dooley, Yanping Gong, Peter A. Kavsak, Edward Randell, Jason L. Robinson, Julie Shaw, Jennifer Taher, Nicole White-Al Habeeb

Bibliographic record

VenueClinical Biochemistry · 2020
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsMount Sinai HospitalMemorial University of NewfoundlandMcMaster UniversityQueen's UniversityUniversity of British ColumbiaHealth PEIKingston Health Sciences CentreUniversity of OttawaCanadian Electricity AssociationIzaak Walton Killam Health CentreMcMaster University Medical CentreUniversity Health NetworkHealth Sciences CentreSunnybrook Health Science CentreDynacast (Canada)Agricultural Research Institute of OntarioDalhousie UniversityUniversity of TorontoB.C. Women's Hospital & Health CentreBrampton Civic Hospital
Fundersnot available
KeywordsInterimSerologyMedicineCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Clinical trialInterim analysisIntensive care medicineMedical physicsImmunologyPathologyAntibodyPolitical scienceDisease

Abstract

fetched live from OpenAlex

Clinical laboratories across the world are working to validate and perform testing for SARS-CoV-2 antibodies. Herein, we present interim consensus guidance for Canadian clinical laboratories testing and reporting SARS-CoV-2 serology, with emphasis on the capabilities and limitations of these tests and recommendations for interpretative comments in an effort to achieve harmonized laboratory practices. The consensus document provides a broad overview of topics including sample type and contamination risk; kinetics of antibody response to COVID-19 and the impact on serology testing; clinical utility of SARS-CoV-2 serology testing; clinical performance of commercial laboratory-based assays commonly deployed in North America; recommendations for interim reporting; utility of SARS-CoV-2 antibody testing for pediatric patients; and utility of point-of-care testing. The information is based on the current literature and is subject to change as additional information becomes available.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.111
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.111
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.463
GPT teacher head0.528
Teacher spread0.065 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2020
Admission routes2
Has abstractyes

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