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Record W2043148474 · doi:10.1637/6067

Trends in Cellulitis Condemnations in the Ontario Chicken Industry Between April 1998 and April 2001

2003· article· en· W2043148474 on OpenAlexaffabout
Sophie St‐Hilaire, William Sears

Bibliographic record

VenueAvian Diseases · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCellulitisBiologySeasonalityVeterinary medicineVariation (astronomy)DemographyAnimal scienceMedicineEcologyImmunology

Abstract

fetched live from OpenAlex

We conducted a retrospective study to determine the prevalence of cellulitis condemnations in the Ontario chicken industry and the relative proportion of variation attributable to factors that vary between processors, producers, and lots and over time. The time span studied was April 1998 to April 2001. We obtained condemnation data randomly from the Chicken Farmers of Ontario and analyzed the data with a generalized mixed model. The (weighted) average prevalence of cellulitis in Ontario between April 1998 and 2001 was 0.94% (0.87%, 1.03%). The prevalence of cellulitis ranged from 0% to 14.9%, with one outlier at 30% and 95% of the data between 0 and 2.58%. The final mixed model we used to describe the variation in the prevalence of cellulitis between lots included random effect terms, the plant where the birds were processed, the producer, the quota period when the birds were processed, and the interaction term quota period by processing plant, as well as fixed effects terms, the type of inspection system and the average weight of the birds. The final model containing these variables explained approximately 78% of the total variation in the data. Our findings indicate all three random effects variables accounted for a significant amount of variation in the cellulitis data; however, the greatest source of variation was ascribed to the plants where the birds were processed. Some of the variation in cellulitis associated with processing plants was explained by the type of inspection system used by the plant, but even after controlling for this factor, there remained a relatively large amount of variation between processing plants (approximately 30%). These findings suggest there may be discrepancies in the diagnoses of the condition. Some of the variation in the prevalence of cellulitis (approximately 13%) was also attributed to the producer; however, more of the variation in the data was attributed to differences in lot-specific factors (approximately 22%). Therefore, future control efforts for cellulitis should focus on standardizing the classification of cellulitis at processing plants and identifying lot specific factors that may increase the risk of the condition.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.112
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.255
Teacher spread0.213 · 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.

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

Citations16
Published2003
Admission routes2
Has abstractyes

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