The relationship between udder skin surface temperature and milk production and composition in dairy cattle (<i>Bos taurus</i> Linnaeus, 1758)
Bibliographic record
Abstract
The aim of the present study was to determine correlations between udder skin surface temperatures and milk yield and estimated composition in dairy cows. The thermographic images of 34 Polish Holstein–Friesian black-and-white cows were taken in a milking parlor before and after milking. Partial correlation coefficients were calculated between the surface temperatures of the udder hind quarters and milk production traits controlling for age, parity, year, and milking time. Daily milk yield was weakly and nonsignificantly correlated with surface temperatures ( rp ranging from −0.19 to 0.21), except for the mean and maximum temperatures of the left hind quarter after milking ( rp = 0.40 and rp = 0.38, respectively). There were significant correlations of skin surface temperature with estimated fat content ( rp = −0.55 to 0.48), protein content ( rp = −0.39 to 0.42), fat yield ( rp = −0.42 to 0.54), and protein yield ( rp = 0.37 to 0.54). The estimated somatic cell count was significantly correlated with the minimum temperature ( rp = −0.54 to −0.36). The estimated urea content was significantly correlated with the minimum temperature ( rp = 0.52). A larger sample size is required in future research to confirm these preliminary results.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".