Hydration in non‐suckling neonatal Brahman‐cross calves
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To identify measures that most closely relate to hydration in healthy Brahman-cross neonatal calves that experience milk deprivation. METHODS: In a dry tropical environment, eight neonatal Brahman-cross calves were prevented from suckling for 2-3 days during which measurements were performed twice daily. RESULTS: Mean body water, as estimated by the mean urea space, was 74±3% of body weight at full hydration. The mean decrease in hydration was 7.3±1.1% per day. The rate of decrease was more than three-fold higher during the day than at night. At an ambient temperature of 39°C, the decrease in hydration averaged 1.1% hourly. Measures that were most useful in predicting the degree of hydration in both simple and multiple-regression prediction models were body weight, hindleg length, girth, ambient and oral temperatures, eyelid tenting, alertness score and plasma sodium. These parameters are different to those recommended for assessing calves with diarrhoea. Single-measure predictions had a standard error of at least 5%, which reduced to 3-4% if multiple measures were used. CONCLUSION: We conclude that simple assessment of non-suckling Brahman-cross neonatal calves can estimate the severity of dehydration, but the estimates are imprecise. Dehydration in healthy neonatal calves that do not have access to milk can exceed 20% (>15% weight loss) in 1-3 days under tropical conditions and at this point some are unable to recover without clinical intervention.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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