Daily variation in the udder surface temperature of dairy cows measured by infrared thermography: Potential for mastitis detection
Why this work is in the frame
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Bibliographic record
Abstract
The daily and within-day variation in udder temperature was monitored in dairy cows (n = 10) using infrared thermography (IRT). The initial assessment and prediction of udder surface temperature variation would hopefully form the basis for future development of an early detection method for mastitis. Our initial objective was to determine the magnitude and pattern of udder temperature variation. To accomplish this, we measured daily fluctuations in udder temperature and the influence of environmental factors upon these values in non-mastitic cows. Udder temperature rose significantly after an exercise period (P < 0.05). Within-day monitoring of udder temperature demonstrated there was a distinct circadian rhythm. Lag regression analysis showed that previous daily udder temperatures together with environmental temperature parameters could successfully predict current udder temperature with a high degree of accuracy. The variation between predicted and actual udder temperature was within the detectable range for an inflammatory response. Infrared thermography shows promise in its application if coupled with environmental temperature monitoring as an early detection method for mastitis. Key words: Thermography, dairy cattle, environment, temperature
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it