Effects of feeding strategy and duration of the dry period on the rumen microbiota of dairy cows
Bibliographic record
Abstract
The composition of rumen microbiota during late gestation and early lactation was compared between cows receiving a close-up diet (1.43 Mcal net energy of lactation (NEl) kg−1 dry matter (DM)) throughout a 40 d dry period (SHORT) and cows receiving a far-off diet (1.28 Mcal NEl kg−1 DM) as well as the close-up diet (as above) for 39 and 21 d, respectively, during a conventional 60 d dry period (CONV). Rumen fluid was collected at weeks −2, −1, +1, +2, and +7 relative to calving. Extracted DNA was analyzed for taxonomic composition of the rumen microbiome using MiSeq Illumina sequencing of the V4 region of the 16S rRNA gene. At week +1, this composition differed (P < 0.05) between treatments. In cows under the CONV treatment, this composition only differed (P < 0.05) between weeks −1 and +1. For SHORT cows, this composition tended to differ between weeks +1 and +2 (P = 0.09) as well as between weeks +2 and +7 (P < 0.03). The change of the taxonomic composition of the rumen microbiota after calving, mainly consisting of increases in the abundance of Firmicutes and decreases in that of Bacteroidites, was comparatively slower and less favourable under the SHORT treatment. This may have been due to more excessive grain intake before calving of cows on the latter treatment.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".