Demographic, Husbandry, and Biosecurity Factors Associated with the Presence of Campylobacter spp. and Tetracycline- and Quinolone- Resistant Campylobacter spp. in Small Poultry Flocks in Ontario, Canada
Bibliographic record
Abstract
Over two years, a surveillance project was conducted to establish the prevalence of poultry and zoonotic pathogens, among small flocks in Ontario, Canada. Our objective was to investigate demographic, husbandry, and biosecurity factors associated with the presence of Campylobacter spp. and antimicrobial-resistant Campylobacter spp. We identified turkeys and mixed housing as risk factors; antibiotic use within the last 12 months, birds having some free-range access, and dedicated clothing use, as protective factors. The effect of pest control depended on the number of birds at risk. We identified the presence of sheep and/or goats on the property and larger flock sizes as having protective effects against tetracycline resistance in Campylobacter isolates and waterfowl and game birds as increasing the odds of quinolone resistance. This work underlines the importance of appropriate disease management methods by small flock owners to prevent and control the zoonotic transmission of Campylobacter spp. and antimicrobial-resistant Campylobacter spp.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".