Detection and characterization of<i>Clostridium difficile</i>in retail chicken
Bibliographic record
Abstract
AIMS: This study was designed to evaluate the prevalence of Clostridium difficile contamination of retail chicken. METHODS AND RESULTS: Chicken legs, thighs and wings were purchased using a standardized method from retail outlets across Ontario, Canada. Selective culture was used for qualitative and quantitative detection of C. difficile. Clostridium difficile was isolated from 26/203 (12.8%) chicken samples; 10/111 (9.0%) thighs, 13/72 (18%) wings and 3/20 (15%) legs (P = 0.19). All isolates were ribotype 078, a strain that has been associated with food animals and potentially community-associated disease in humans. All positive samples were positive only on enrichment culture. CONCLUSIONS: Clostridium difficile could be found relatively commonly in retail chicken meat, albeit at low levels. SIGNIFICANCE AND IMPACT OF THE STUDY: This is the first study to report C. difficile in chicken meat. Contamination of meat with C. difficile strains implicated in human infections raises concerns about food as a source of C. difficile infection. The relevance of food contamination is completely unclear at this point but food should be investigated as a source of infection.
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 | 0.000 | 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) | 0.001 | 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".