Development of Ruminal and Fecal Microbiomes Are Affected by Weaning But Not Weaning Strategy in Dairy Calves
Bibliographic record
Abstract
The nature of weaning, considered the most stressful and significant transition experienced by dairy calves, influences the ability of a calf to adapt to the dramatic dietary shift, and thus, can influence the severity of production losses through the weaning transition. However, the effects of various feeding strategies on the development of rumen or fecal microbiota across weaning are yet to be examined. Here we characterized the pre- and post-weaning ruminal and fecal microbiomes of Holstein dairy calves exposed to two different weaning strategies, gradual (step-down) or abrupt. We describe the shifts toward a mature ruminant state, a transition which is hastened by the introduction of the solid feeds initiating ruminal fermentation. Additionally, we discuss the predicted functional roles of these communities, which also appear to represent that of the mature gastrointestinal system prior to weaning, suggesting functional maturity. This assumed state of readiness also appeared to negate the effects of weaning strategy on ruminal and fecal microbiomes and therefore, we conclude that the shift in gastrointestinal microbiota may not account for the declines in gain and intakes observed in calves during an abrupt weaning.
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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 | 0.000 | 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) | 0.001 | 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".