Frequency and Enumeration of Campylobacter Species from Processed Broiler Carcasses by Weep and Rinse Samples
Bibliographic record
Abstract
Frequency and numbers of Campylobacter spp. were assessed per freshly processed, contaminated broiler carcass. Campylobacter-positive flocks were identified by cecal sample analysis at slaughter. These flocks had been tested as Campylobacter negative at 4.1 +/- 0.9 d prior to slaughter. Levels of contamination were estimated using 2 sampling approaches per carcass: (1) free weep fluids and (2) whole-carcass, 100 mL of distilled water rinses. Estimations of counts were determined by directly plating dilutions of weeps and rinses onto Campy-Cefex agar and incubating the plates at 41.5 degrees C under microaerobic atmosphere. Confirmation was provided by latex agglutination to quantify levels per milliliter of weep and per 100 mL of rinse. Thirty-two slaughter groups ( approximately 20 carcasses per group) were compared from 2003 to 2004. The Campylobacter-positive weep frequency was 84.8%, whereas the frequency for rinse samples was 74.4% (P < 0.001). Enumeration of Campylobacter spp. on positive samples ranged from 0.70 to 6.13 log(10) cfu/mL of weep (geometric mean of 2.84) and from 2.30 to 7.72 log(10) cfu/100 mL of rinse (geometric mean of 4.38). The correlations between weep and rinse were 0.814 with 0.5 mL of rinse and 0.6294 when applying 0.1 mL of rinse The quantitative regression analyses for these 2 corresponding tests were log(10) rinse (for 0.5 mL of inoculum) = 1.1965 log(10) weep + 0.4979, and log(10) rinse (for 0.1 mL of inoculum) = 1.322 log(10) weep - 0.1521. FlaA SVR sequencing of isolates indicated that the same genotypes were found in weep and rinse samples. Weep and rinse sampling led to different proportions of Campylobacter-positive carcasses detection, but we demonstrated that this difference was reduced by increasing the amount of rinse fluid used for plating.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".