Growth and Blood Parameters of Weaned Crossbred Beef Calves Fed Forage Kale (<i>Brassica oleracea</i>spp.<i>acephala</i>)
Bibliographic record
Abstract
Forty lightweight calves ( 206.4 ± 3.2 kg) were randomly distributed to four treatments: (Control) low nutritive value pasture and hay plus 1 kg d −1 of rolled barley; (Pasture) management intensive pasture; (Haylage) timothy haylage; and (Kale) 50% timothy haylage −50% kale pasture. Blood samples were analysed for thyroid hormones, liver enzymes, glucose, cholesterol, total proteins (TP), albumin, globulins, and urea-N. At the end of the trial, the Pasture group was the heaviest with 323.6 ± 4.2 kg BW and 1.54 kg ADG. Final BW and ADG were similar for the Kale and Haylage groups. Blood T 3 was higher for Kale than for the other groups. The T 3 /T 4 ratio was greater for Control at the end of the experiment. There were no treatment differences for T 4 , aspartate aminotransferase (AST), gamma glutamyl transferase (GGT), glutamate dehydrogenase (GLDH), cholesterol, and glucose. Blood urea-N was lower for Kale and higher for Pasture; however albumin concentrations were greater for Pasture and similar for other treatments. Except for the Control group, calves had a lower concentration of circulating globulins at the end than at the beginning of the experiment. This study showed that Kale could be fed to backgrounding calves without detrimental effects on performance.
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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 | 0.000 | 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 | 0.001 |
| 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".