Clostridium difficile in Retail Meat Products,
Bibliographic record
Abstract
To determine the presence of Clostridium diffi cile, we sampled cooked and uncooked meat products sold in Tucson, Arizona. Forty-two percent contained toxigenic C. diffi cile strains (either ribotype 078/toxinotype V [73%] or 027/ toxinotype III [NAP1 or NAP1-related; 27%]). These fi ndings indicate that food products may play a role in interspecies C. diffi cile transmission. The incidence and severity of Clostridium diffi cile infections (CDIs) are increasing in North America (1), probably because of emergence of an epidemic strain (NAP1/ BI/027, toxinotype [TT] III) (2,3). C. diffi cile transmission occurs primarily in healthcare facilities, but community-associated CDI (CA-CDI) appears to be increasing and may now account for 20%–45 % of positive diagnostic assay results (4,5). Up to 35 % of patients with CA-CDI report no antimicrobial agent use within 3 months before disease onset (4,5), although nonantimicrobial drugs (e.g., proton pump inhibitors, nonsteroidal antiinflammatory agents) are also implicated as risk factors (4). Sources of C. diffi cile acquisition in community settings are unknown. CDI is increasingly important in food animals (6). Infection rates of>95 % have been documented among neonatal pigs in farrowing facilities, resulting in diarrhea and typhlocolitis (6). Toxigenic C. diffi cile is also implicated as a cause of diarrhea in calves (7). C. diffi cile was identified in raw meat intended for pet consumption (8) and in ≈20% of retail ground beef in Canada (9). We report the isolation of C. diffi cile from uncooked and ready-to-eat meats in retail markets in a US metropolitan area.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 0.001 |
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".