Additional file 2 of Seasonal stability of the rumen microbiome contributes to the adaptation patterns to extreme environmental conditions in grazing yak and cattle
Bibliographic record
Abstract
Additional file 2: Fig. S1. The dynamic changes of Bray-Curtis distance between yak (n=6) and cattle (n=6) at different seasons. (A) Bacterial community similarity among different seasons between yak and cattle. (B) Archaeal community similarity among different seasons between yak and cattle. Statistical analysis was determined using the non-parametric Kruskal-Wallis test in combination with Dunn’s post-doc test for multiple comparisons, and P values were corrected by Benjamin-Hochberg algorithm (* 0.05 < P < 0.01, ** 0.01 < P < 0.001, *** P < 0.001). Fig. S2. Non-metric multidimensional scaling (NMDS) analysis plot based on Bray–Curtis metrics showed fungal (A) and protozoal (B) community (at species level) of grazing yak and cattle at different seasons. (C) Fungal community similarity between cattle and yak. (D) Protozoal community similarity between cattle and yak. Fig. S3. Significantly different (P < 0.05) bacterial phyla between cattle and yak across seasons. Significantly different was assessed by non-parametric Kruskal-Wallis test in combination with Dunn’s post-doc test for multiple comparisons. Fig. S4. CAZyme profiles of yak and cattle. (A) Venn diagrams displaying overlap and unique CAZymes between yak and cattle. (B) Seasonal shift of CAZyme profiles in yak and cattle. Venn diagrams were generated using Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/). Fig. S5. Profiles of rumen microbiota origin of observed ARGs and CAZymes. (A) Venn diagrams showing overlap and unique rumen bacteria host both ARGs and CAZymes between yak and cattle. (B) Seasonal profile of rumen bacteria host both ARGs and CAZymes between yak and cattle. Venn diagrams were created by Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/), the taxonomic information of sequences (host both ARGs and CAZymes) were obtained by aligning the corresponding contigs to rumen metagenome-assembled genomes (MAGs) [5] using Kraken2 [113]. Fig. S6. Comparison of bacterial (A) and archaeal (B) alpha diversity indices between the current study (cattle and yak) and other studies. (* 0.05 < P < 0.01, ** 0.01 < P < 0.001, *** P < 0.001). Studies 1-4 indicates that the published studies. Fig. S7. Rumen bacterial species significantly differed in relative abundances between the current study (cattle and yak) and other studies. Studies 1-4 indicates that the published studies. Fig. S8. Rumen microbial functions (KEGG pathways: A; CAZyme families: B) that significantly differed in relative abundances between the current study (cattle and yak) and other studies. Studies 1-4 indicates that the published studies.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.845 | 0.109 |
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".