Composition, spatial distribution, and diversity of the bacterial communities in the rumen of cows fed different forages
Bibliographic record
Abstract
The species composition, distribution, and biodiversity of the bacterial communities in the rumen of cows fed alfalfa or triticale were investigated using 16S rRNA gene clone library analyses. The rumen bacterial community was fractionated and analyzed as three separate fractions: populations in the planktonic, loosely attached to rumen digesta particles, and tightly attached to rumen digesta particles. Six hundred and thirteen operational taxonomic units (OTUs) belonging to 32 genera, 19 families, and nine phyla of the domain Bacteria were identified from 1014 sequenced clones. Four hundred and fifty one of the 613 OTUs were identified as new species. These bacterial sequences were distributed differently among the three fractions in the rumen digesta of cows fed alfalfa or triticale. Chao 1 estimation revealed that, in both communities, the populations tightly attached to particulates were more diverse than the planktonic and those loosely attached to particulates. S-Libshuff detected significant differences in the composition between any two fractions in the rumen of cows with the same diet and between the communities fed alfalfa and triticale diets. The species richness estimated for the communities fed alfalfa and triticale is 1027 and 662, respectively. The diversity of the rumen bacterial community examined in this study is greater than previous studies have demonstrated and the differences in the community composition between two high-fiber diets have implications for sample selection for downstream metagenomics applications.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".