Comparison of results for commercially available microbiological media plates with results for standard bacteriologic testing of bovine milk
Bibliographic record
Abstract
OBJECTIVE: To compare results for 3 commercially available microbiological media plates with those for standard bacteriologic testing of bovine milk. SAMPLE: Milk samples from postpartum cows and cows with a high somatic cell count (SCC) or clinical mastitis (CM). PROCEDURES: Sample-ready Staphylococcus culture medium (SRSC) plates were used to detect Staphylococcus aureus in milk samples obtained from postpartum cows and cows with a high SCC or CM. Rapid coliform count (RCC) plates were used to detect coliforms in milk samples obtained from cows with CM. Aerobic count (AC) plates were used to detect streptococci in CM samples. Fresh mastitic milk samples were frozen and then thawed to evaluate the effects of freezing for the SRSC and RCC plates. The effects of dilution (1:10) of samples were determined. Agreement of results between the commercially available plates and standard bacteriologic testing was evaluated. RESULTS: The ability of SRSC plates to detect S aureus in milk samples was highest with diluted samples from postpartum cows and cows with a high SCC or CM. Sensitivity of the RCC plate for detection of coliforms was highest with diluted mastitic milk samples. The AC plates had a poor positive predictive value for detection of streptococci in mastitic milk samples. Freezing increased S aureus detection. CONCLUSIONS AND CLINICAL RELEVANCE: Overall, the SRSC and RCC plates were accurate, were easy to use, and yielded results comparable to those of standard bacteriologic testing for the detection of S aureus and coliforms in bovine milk.
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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".