Month-Wise Prevalence of Subclinical Mastitis in Dairy Cows in Guangdong Province, China
Bibliographic record
Abstract
To evaluate the month-wise prevalence of subclinical mastitis (SM) and its relations with climatic temperature and humidity, and to provide references for control and prevention of mastitis in dairy cows in Guangdong, China, California mastitis test method was used to determine the monthly prevalence of SM (MPSM, %) of lactating Holstein cows from 11 dairy farms in Guangdong Province, China, including about 516 cows per monthly examination. The average MPSM on a cow and a quarter basis were 30 and 13% respectively, and there was a positive linear correlation between monthly mean air temperature (MT, ?C) and MPSM on a cow basis (r=0.763, P=0.004) or a quarter basis (r=0.577, P=0.049), but there were no correlations between MT and MPSM on a cow or a quarter basis (P>0.05). There was a shift in MPSM trend that the highest MPSM (38.4%) was not for the hottest July with MT at 30.8?C, but for the later September at 27.9?C. The farms need to develop new housing conditions to control cowshed temperatures in the hot season to reduce the mastitis prevalences in the posthot months.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".