Short communication: Diagnostic performance of on-farm bacteriological culture systems for identification of uterine Escherichia coli in postpartum dairy cows
Bibliographic record
Abstract
The objectives of this study were to validate the performance of on-farm bacteriological culture systems for identification of Escherichia coli in the uterus of early postpartum dairy cows and to determine if an association is present between the results and the subsequent occurrence of puerperal metritis (PM). A prospective cohort study was conducted in one commercial Holstein dairy herd in which 400 cows were sampled between 24 and 48 h after parturition. Three bacteriological samples were obtained from the uterus of each cow and were cultured for identification of E. coli. One sample was cultured in a commercial bacteriology laboratory according to standard procedures for identification of E. coli and was considered as the reference test. The two other samples were cultured on the farm using the Tri-Plate (University of Minnesota, St. Paul, MN) and Petrifilm systems, and plate readings were done after 24 and 48 h of incubation (variables: Tri24h, Tri48h, Petri24h, Petri48h). Participating cows were followed until 21 days in milk to diagnose PM. The prevalence of PM and E. coli (from the reference test) in the cow population was 15.0 and 33.5%, respectively. Both on-farm culture systems were accurate compared with the reference test. The sensitivity and specificity were 97 and 100%, 99 and 100%, 100 and 92%, and 100 and 89% for Tri24h, Tri48h, Petri24h, and Petri48h, respectively. On-farm results for Tri24h, Tri48h, Petri24h, and Petri48h were associated with subsequent occurrence of PM. The results from this study support the use of the Tri-Plate and Petrifilm culture systems on dairy farms to identify the presence of E. coli in the uterus of postpartum cows.
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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 | 0.004 | 0.013 |
| 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 | 0.001 | 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".