Postprandial Metabolism and Endocrine Status in Veal Calves Fed at Different Frequencies
Bibliographic record
Abstract
Veal calves fed by bucket often develop postprandial insulin resistance, hyperglycemia, and glucosuria during fattening. Automatic feeding systems allow feed intake for 24 h, and small ingested portions are expected to decrease postprandial glucose loads. We have studied metabolic and endocrine traits in calves that were either 1) fed identical daily amounts of whole milk plus milk replacer by a computer-programmed automatic feeder (> or =6 portions from 0800 to 2400 h) (GrA) or 2) fed by bucket at 0800 and 1630 h (GrB). Calves started at a body weight of 118 kg, and the experiment lasted for 3 wk. During wk 3, lactose was supplemented to stress postabsorptive glucose homeostasis. Feed intake and average daily gains in GrA and GrB were similar. Plasma concentrations during an 8-h period of glucose (in part), lactate, urea, and somatostatin (in wk 3), and of glucagon and insulin (wk 2 and 3) were smaller in GrA than in GrB, whereas growth hormone, insulin-like growth factor I, insulin-like growth factor binding protein-1 (wk 2), and prolactin concentrations (wk 2 and 3) were higher. Lactose supplementation in wk 3 enhanced transient postprandial hyperglycemia and hyperinsulinemia. Thus, there were marked metabolic and endocrine differences when calves sucked their feed in six or more portions during a 16-h period from an automatic feeder compared with twice daily drinking from a bucket. Ingestion of small portions by calves avoided marked hyperglycemia and lactate increments, and lower plasma urea concentrations mirrored enhanced nitrogen utilization, possibly mediated by the altered growth hormone, IGF-I and insulin status.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".