Differential effects of sodium and magnesium sulfate on water consumption by beef cattle1,2
Bibliographic record
Abstract
The existing guidelines for maximum sulfate (SO4) in cattle drinking water are based on Na2SO4, although many water sources contain greater concentrations of MgSO4. Two experiments compared the effect of different SO4 salts on water consumption and fecal DM of cattle. In Exp. 1, 8 yearling heifers (initial BW = 345 +/- 8 kg; mean +/- SD) were watered twice daily with tapwater or water containing Na2SO4 or MgSO4 at target levels of 1,500, 3,000, or 4,500 mg of SO4/L for 2-d treatment periods separated by 2 d of access to tapwater. In Exp. 2, 16 yearling cattle (initial BW = 421 +/- 24 kg) were watered twice daily with tap-water (16 mg of SO4/L) or water containing Na2SO4 at target levels of 2,000 mg of SO4/L (low Na2SO4), MgSO4 at 2,000 mg of SO4/L (low MgSO4), or MgSO4 at 4,000 mg of SO4/L (high MgSO4) in 21-d treatment periods separated by 7-d periods on tapwater. The first 10 d of each period were allowed for adjustment to the treatment, and the final 11 d was considered the treatment period for analysis purposes. Treatments were applied in an incomplete Latin square, where each animal was exposed to 3 of the 4 treatments. In Exp. 1, the average daily water consumption decreased linearly as the SO4 concentration increased for MgSO4 (P = 0.0001) but not for Na2SO4 (P = 0.39). In Exp. 2, the average daily water consumption was less for cattle on the high-MgSO4 treatment than for cattle on the low-MgSO4 treatment (P = 0.0001), and cattle on the low-MgSO4 treatment tended (P = 0.09) to drink less than those on the tap-water treatment. Fecal DM was greater for cattle on the high-MgSO4 treatment than for those on the low-MgSO4 treatment (P < 0.01). These findings indicate that cattle reduce their consumption of water containing high (> or = 4,000 mg of SO4/L) concentrations of MgSO4, even after a given time to adjust to the treatment; such reductions may be accompanied by an increase in fecal DM.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".