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Record W4321003199 · doi:10.1093/lambio/ovac057

Evaluating iQ-CheckTM real-time PCR to detect <i>Salmonella</i> from poultry environmental samples in Fraser Valley, British Columbia, Canada

2022· article· en· W4321003199 on OpenAlexaffabout
Ethan Kenmuir, Daniel M. Knowles, Giselle Hughes, Jaime Battle, Kazal Ghosh

Bibliographic record

VenueLetters in Applied Microbiology · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsMinistry of Agriculture
FundersLandbruks- og matdepartementet
KeywordsSalmonellaTurnaround timePoultry farmingLivestockVeterinary medicineBiologyBiotechnologyEnvironmental healthEnvironmental scienceEcologyOperations managementBacteriaMedicineEngineering

Abstract

fetched live from OpenAlex

Salmonella is a ubiquitous pathogen that accounts for foodborne and livestock illnesses worldwide. Robust surveillance programs must be implemented to maintain human and animal health and limit economic losses. The poultry industry in particular demands the implementation of rapid Salmonella detection methods that will facilitate the timely availability of results in a manner allowing actions to be taken for the associated poultry products. One such method, the iQ-CheckTM real-time PCR, has significantly reduced turnaround times compared to conventional culture methods. In this study, a total 733 poultry environmental samples was received from farms in the Fraser Valley of British Columbia, Canada and the real-time PCR method was assessed for its ability to detect Salmonella in comparison to the currently used culture protocol. The iQ-Check real-time PCR method was effective at accurately screening out the majority of negative samples, and demonstrated a very strong correlation with the culture method. This was especially true when selective enrichment was performed before PCR, with sensitivity, specificity, and accuracy values reaching 100.0%, 98.5%, and 98.9%, respectively. These results demonstrate that rapid detection methods could be effectively introduced into current Salmonella surveillance workflows dealing with environmental poultry samples to reduce turnaround times and minimize economic impacts on producers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.201
Teacher spread0.187 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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