Short communication: Diagnostic accuracy of the Petrifilm culture system for identifying colostrum with excessive bacterial contamination in Quebec dairy herds
Bibliographic record
Abstract
The objective of this study was to validate the diagnostic accuracy of the Petrifilm culture system (3M, St. Paul, MN) for identifying colostrum with excessive bacterial contamination. An observational cross-sectional study was conducted between October 2015 and February 2016. Two colostrum aliquots were collected during the first meal of 332 calves (33 commercial Holstein dairy farms) in Quebec, Canada. One aliquot per calf was used to quantify the total bacteria count and the total coliform count using standard bacteriological laboratory testing (reference test). These results were dichotomized to identify colostrum with excessive bacterial contamination [aerobic count plate (AC) >100,000 cfu/mL; coliform count plate (CC) >10,000 cfu/mL]. The Petrifilm system was used to quantify both aerobic and coliform contamination of the other colostrum aliquot from each calf. As such, AC and CC were used according to the manufacturer's recommendations. The area under the curve of the receiver operating characteristic curve of AC and CC compared with the laboratory were 0.83, and 0.95, respectively. Using the optimal threshold of >24,000 cfu/mL for AC results, the Petrifilm system had a sensitivity (Se) of 69%, specificity (Sp) of 86%, and a kappa value of 0.54. Using the optimal threshold of >4,000 cfu/mL for CC results, the Petrifilm system had a Se of 93%, Sp of 90%, and kappa value of 0.64. Overall, these results suggest that the Petrifilm system is an appropriate alternative for identifying colostrum with excessive bacterial contamination.
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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 | 0.003 | 0.009 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".