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Record W7129443982 · doi:10.51847/o7gfl1vzrn

Enhancing Accuracy of SARS-CoV-2 Point-of-Care Testing Through Proficiency Testing: Experiences from a Provincial EQA Program in Canada

2025· article· W7129443982 on OpenAlexaboutno aff
Sarah Louise Peterson, Emily Kathleen Rogers

Bibliographic record

VenueJournal of Medical Sciences and Interdisciplinary Research · 2025
Typearticle
Language
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsnot available
Fundersnot available
KeywordsIdentification (biology)Coronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Diagnostic testTest (biology)Primary careProgram evaluation

Abstract

fetched live from OpenAlex

During the coronavirus disease 2019 (COVID-19) pandemic, the rapid expansion of diagnostic capacity prompted the Canadian Microbiology Proficiency Testing (CMPT) program to establish a new proficiency testing (PT) scheme dedicated to molecular and antigen-based identification of SARS-CoV-2. This initiative specifically targeted point-of-care testing (POCT) locations operating within the eight provincial Health Authorities of British Columbia (BC), Canada, with the primary objective of evaluating

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)0.009
metaresearch head score (Gemma)0.037
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.002
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 head0.182
GPT teacher head0.486
Teacher spread0.304 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations5
Published2025
Admission routes1
Has abstractyes

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