Short communication: Feed sorting of dairy heifers is influenced by method of dietary transition
Bibliographic record
Abstract
This study investigated the effect of exposing heifers to individual feed components on the extent and pattern of feed sorting upon transition to a novel ration. Holstein heifers (394 ± 62 d old, weighing 409.8 ± 37.3 kg; mean ± SD), consuming a familiar mixed silage-based ration [55% corn silage and 45% haylage, dry matter (DM) basis], were transitioned to a novel total mixed ration [TMR; 41.6% haylage, 36.5% corn silage, 14.6% high-moisture corn, and 7.3% protein supplement, DM basis] by 1 of 2 treatments: direct transition to novel TMR (DIR; n = 5) or exposure to novel TMR components individually before receiving novel TMR (COM; n = 6). During the baseline period (d 1 to 4), all heifers were offered the familiar silage-based ration. During transition (d 5 to 12), DIR heifers received the novel TMR, whereas COM heifers received the novel TMR components offered separately, in amounts according to TMR composition (target 15% orts). After transition (d 13 to 20), all heifers received the novel TMR. Feed intake and feeding time were determined daily and fresh feed and individual orts were sampled every 2d for particle size analysis and neutral detergent fiber content. The particle size separator consisted of 3 screens (18, 9, and 1.18 mm) and a bottom pan, resulting in 4 fractions (long, medium, short, and fine). Sorting activity for each fraction was calculated as actual intake expressed as a percentage of predicted intake. We detected no effect of treatment on dry matter intake or feeding time. After transition to the novel TMR, COM heifers sorted to a greater extent than did DIR heifers, sorting against long particles (95.4 vs. 98.9%) and for short particles (101.7 vs. 100.6%). Differences in sorting patterns resulted in COM heifers tending to have lower neutral detergent fiber intake as a percentage of predicted intake (98.9 vs. 100.5%). The results of this study suggest that the degree of feed sorting may be influenced by method of transition to a novel ration.
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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".