MétaCan
Menu
← Back to cohort

Comparison of bacterial culture, PCR and a mix-ELISA for the detection of Salmonella status in nursery and grow-to-finish pigs in Western Canada using a Bayesian approach

2009· article· en· W323046346 on OpenAlexaffabout
Wendy Wilkins, Cheryl Waldner, Andrijana Rajić, Margaret McFall, Eudora Y. Chow, Anne Muckle, R. C. M. Jaime

Bibliographic record

VenueInternational Conference on the Epidemiology and Control of Biological, Chemical and Physical Hazards in Pigs and Pork · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsUniversity of Prince Edward IslandAgriculture Food and Rural DevelopmentPublic Health Agency of CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsSalmonellaBayesian probabilityMicrobiological cultureSerotypeComputer scienceBiologyMicrobiologyArtificial intelligenceBacteriaGenetics

Abstract

fetched live from OpenAlex

Bayesian and traditional statistical methods were used to estimate accuracy of bacterial culture, broth-enriched real-time-PCR for feces and a mix-ELISA (Svanovir®) for serum to detect Salmonella in nursery and grow-finish pigs on 10 fanns in western Canada. In nursery pigs, one pooled pen fecal sample and one blood sample were taken from each of 30 randomly selected pens. In grow-finish pigs, samples were similarly collected; an individual fecal sample was also taken from each pig bled. Only 8/247 ELISA-positive nursery pigs were detected; 80/247 pens were culture positive. Since there was no agreement between pen culture and ELISA results in the nursery pigs, further evaluation of test accuracy was not possible at this level. Among grow-to-finish pigs, agreement between culture and ELISA was fair (K=0.26-0.38). Agreement between culture and the RT-PCR was nearly perfect ( K=0.92-0.97).

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.071
GPT teacher head0.321
Teacher spread0.249 · 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 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
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueInternational Conference on the Epidemiology and Control of Biological, Chemical and Physical Hazards in Pigs and Pork→Same topicSalmonella and Campylobacter epidemiology→French-language works237,207→