Additional file 1 of Short- and long-term dietary supplementation as well as withdrawal of the enteric methane inhibitor 3-nitrooxypropanol reveal distinct effects on the rumen microbial community
Bibliographic record
Abstract
Additional file 1: Table S1. Ingredient and chemical composition of the basal diet in the short-term study. Table S2. Ingredient and chemical composition of the basal diet in the long-term study. Additional file 2: Table S3. Pairwise comparisons of beta diversity of bacterial, archaeal, and protozoal communities after short-term 3-NOP supplementation in beef cattle. Table S4. Pairwise comparisons of beta diversity of bacterial, archaeal, and protozoal communities after long-term 3-NOP supplementation in beef cattle. Table S5. Effects of short-term 3-NOP supplementation on rumen microbial taxa (bacteria, archaea, and protozoa) based on relative and estimated absolute abundances. Table S6. Effects of long-term 3-NOP supplementation on rumen microbial taxa (bacteria, archaea, and protozoa) based on relative and estimated absolute abundances. Table S7. Effects of long-term 3-NOP supplementation and withdrawal on rumen microbial taxa (bacteria, archaea, and protozoa) based on relative and estimated absolute abundances. Table S8. Effects of short-term 3-NOP supplementation on predicted rumen functions based on CowPI. Table S9. Effects of long-term 3-NOP supplementation on predicted rumen functions based on CowPI. Table S10. Summary of microbial co-occurrence network metrics in the short-term 3-NOP supplementation. Table S11. Summary of microbial co-occurrence network metrics in the long-term 3-NOP supplementation.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.852 | 0.129 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".