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Record W4292679772 · doi:10.1038/s41598-022-17590-5

Author Correction: Emergence of a mutation in the nucleocapsid gene of SARS-CoV-2 interferes with PCR detection in Canada

2022· erratum· en· W4292679772 on OpenAlexaffabout
Sandra Isabel, Mariana Abdulnoor, Karel Boissinot, Marc R Isabel, Richard de Borja, Philip C. Zuzarte, Calvin Sjaarda, Kevin R. Barker, Prameet M. Sheth, Larissa Matukas, Jonathan B. Gubbay, Allison McGeer, Samira Mubareka, Jared T. Simpson, Ramzi Fattouh

Bibliographic record

VenueScientific Reports · 2022
Typeerratum
Languageen
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsSinai Health SystemSunnybrook HospitalLunenfeld-Tanenbaum Research InstituteTrillium Health CentreQueen's UniversitySt. Michael's HospitalOntario Institute for Cancer ResearchHospital for Sick ChildrenKingston Health Sciences CentrePublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyCoronavirus disease 2019 (COVID-19)MutationGene2019-20 coronavirus outbreakGeneticsComputational biologyBiologySars virusMedicineInternal medicine

Abstract

fetched live from OpenAlex

The original version of this Article contained an error in the spelling of the author Allison J. McGeer which was incorrectly given as Alisson J. McGeer.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.043
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0040.001
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0220.017

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 head0.040
GPT teacher head0.321
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2022
Admission routes2
Has abstractno

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