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Comparison of sample pretreatments used to distinguish between infectious and non-infectious foodborne viruses by RT-qPCR

2025· article· en· W4407856785 on OpenAlexafffund
Anne-Marie Lauzier, Émilie Douette, Antoine Labrie, Éric Jubinville, Valérie Goulet-Beaulieu, Fabienne Hamon, Julie Jean

Bibliographic record

VenueJournal of Virological Methods · 2025
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsBiologyVirologyInfectious disease (medical specialty)MicrobiologyFood microbiologyBacteriaGenetics

Abstract

fetched live from OpenAlex

), magnetic silica beads and centrifugal filter using HAV or HuNoV inactivated by heat, pulsed light, or sodium hypochlorite (NaOCl). PMAxx completely or nearly eliminated (3.96 ± 1.24 log gc) the RT-qPCR signal of HAV inactivated at 100°C for 10 min. Pretreatments could not reduce significantly RT-qPCR signal of HAV after pulsed light (0.74 ± 0.36 log gc) and NaOCl (0.24 ± 0.14 log gc) inactivation. Enzymatic treatments did not improve the results obtained with PMAxx. The exudate of raspberry, strawberry or oyster used as food matrices needed dilution by at least tenfold for PMAxx to to yield results comparable to virions without a food matrix. Overall, PMAxx shows good potential to discriminate between infectious and non-infectious despite some remaining limitations.

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)0.002
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.120
GPT teacher head0.520
Teacher spread0.399 · 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 designObservational
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

Citations6
Published2025
Admission routes2
Has abstractyes

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