Additional file 5 of An integrated gene catalog and over 10,000 metagenome-assembled genomes from the gastrointestinal microbiome of ruminants
Bibliographic record
Abstract
Additional file 4: Table S10. Comparison of the levels of COG functional modules of the microbiome across the ruminant GIT regions. Table S11. Comparison of the levels of KO functional modules of the microbiome across the ruminant GIT regions. Table S12. Comparison of the levels of CAZyme functional modules of the microbiome across the ruminant GIT regions. Table S13. Quality information and assessment of 28,543 MAGs produced in this study. Table S14. Bins that aligned to fungal or protozoan genomes from GenBank. Table S15. Quality information for 310,661 viral contigs generated from our dataset. Table S16. Genomic statistics for 10,373 nonredundant MAGs from our dataset. Table S17. Taxonomic classification and genome properties of 367 MAGs aggregated in Module 47 of Fig. 4. Table S18. Taxonomic information for the top 10 Hub genomes in each GIT region. Table S19. The 41,369 bacterial, 2,163 archaeal, 2,647 fungal and 468 protozoan reference genomes from GenBank used in this study. Table S20. Collection of 7,052 previously published ruminant microbial genomes. Table S21. Quality assessment and taxonomic classification of 8,745 uncultured candidate bacterial and archaeal species. Table S22. Read classification rate of 635 published metagenomic samples and 370 GIT samples in this study using GenBank, RMG and USG. Table S23. The 850,749 CAZyme-predicted proteins from the 8,745 USGs listed in Additional file 4: Table S18. Table S24. The 12,578 predicted PULs and taxonomic classification of 1,772 USGs. Table S25. Number and characteristics of biosynthetic gene clusters identified in the USGs. Table S26. Comparison of GPs in the genomes assigned to the phylum Proteobacteria. Table S27. Taxonomic classification and distribution of 160 archaeal MAGs among the GIT regions. Table S28. Taxonomic classification and counts of predicted hydrogenases among the 6,152 MAGs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.718 | 0.162 |
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".