Validation of commercial luminometry swabs for total bacteria and coliform counts in colostrum-feeding equipment
Bibliographic record
Abstract
A sufficient quantity and quality of colostrum must be fed quickly to the newborn calf while minimizing bacterial contamination. Adenosine triphosphate bioluminescence swabs offer a potential rapid on-farm alternative to assess bacterial contamination of colostrum. The objective of this study was to validate the Hygiena (Camarillo, CA) AquaSnap Total (AS), SuperSnap (SS), PRO-Clean (PC), and MicroSnap Coliform (MS) swabs as well as visual hygiene assessment for detection of elevated bacterial counts in or on colostrum-feeding equipment. From April to October 2016, 18 esophageal tube feeders, 49 nipple bottles, and 6 pails from 52 dairy farms in Ontario were evaluated for cleanliness. Following visual hygiene assessment, sterile physiological saline (15 mL) was poured into each piece of equipment, mixed for 2 min to ensure total surface coverage, and poured into a sterile collection container through the feeding end. The fluid was split into equal aliquots, with one being evaluated by conventional culture and the other evaluated using the luminometry swabs. Nonparametric receiver operator curves were used to compare the test performance of the luminescence reading (relative light units; RLU) from each type of swab to conventional bacterial culture. The area under the curve comparing the AS swab to total bacterial count (cut point >100,000 cfu/mL) was 0.89, and using a cut point of 631 RLU correctly classified 84% of samples with a sensitivity of 88% and a specificity of 77%. The area under the curve comparing the MS swab to total coliform count (cut point >10,000 cfu/mL) was 0.85, and using a cut point of 44 RLU correctly classified 89% of samples with a sensitivity of 83% and a specificity of 90%. Visual hygiene assessment, PC and SS swabs were not reliable indicators for feeding equipment cleanliness. The results suggest that the AS and MS swabs can be used as an alternative to traditional laboratory bacterial counts to evaluate cleanliness of colostrum-feeding equipment.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".