Can diet change the diversity of ruminal bacterial species in beef cattle?
Bibliographic record
Abstract
Abstract Background The objective of this study was to assess the effects of diet on bacterial species in the solid fraction of the ruminal content using the gene sequences of the conserved 16S rDNA region steers fed one of the following diets: canola (C), cottonseed (A), sunflower (G), soybean (SO), corn silage (S) and control diet (PD). Canola, cottonseed, sunflower and soybean were fed as whole seeds. Six crossbred steers (Body weight = 416.33 ± 93.30 kg; mean ± SD), castrated male, and fitted with ruminal cannula were used. The experimental design was a 6 × 6 Latin square design. Results Cellulolytic bacteria were predominant for all diets, with 47.75% of Operational Taxonomic Units (OTU) in animals fed the cottonseed diet. Amylolytic bacteria were identified for all diets, representing 62.51% OTU in animals consuming the sunflower diet. Proteolytic bacteria were identified for all diets, corresponding to 65.96% OUT in animals fed the sunflower diet. Lactic bacteria were identified for all diets. Megasphaera elsdenii bacterium was identified for all diets, with a greater diversity of this bacterium in steers fed the control diet. This bacterium may reduce the availability of hydrogen in the rumen due to propionate production and lactate utilization. Conclusion Oilseed in the diet showed a similarity of bacteria species with 47.5% of changing of the ruminal flora.
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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 | 0.000 |
| 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".