Validation of two diagnostic methods for postpartum endometritis in dairy cows
Bibliographic record
Abstract
Postpartum uterine diseases can impair reproductive performance of dairy cows. Diagnostic tools have been developed to identify cows at risk of poor subsequent reproductive performance. Most of these tools focus on identification of inflammation in the reproductive tract during the postpartum period. Endometrial cytology was proposed as a good tool to identify cows with cytological endometritis; however, cytology is not an easy technique to implement for an on-farm uterine health surveillance program in dairy herds because it requires the use of a microscope. Therefore, a more convenient on-farm method needs to be identified for determination of uterine status of dairy cows. Aleucocyte esterase (LE) colorimetric test is commercially available (Multistix®, Bayer Corporation, Elkhart, IN) and could be used to detect endometrial inflammation. The objectives of this study were to determine diagnostic criteria for endometritis in dairy cows by use of endometrial cytology and LE testing, to quantify the agreement between results of these two methods, and to quantify their impact on subsequent reproductive performance.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".