Additional file 1 of Genome-centric metagenomics reveals the host-driven dynamics and ecological role of CPR bacteria in an activated sludge system
Bibliographic record
Abstract
Additional file 1: Table S1. Summary of 43 CPR markers used by CheckM for genome quality estimation. Table S2. Summary of the studied CPR MAGs in the present study. Table S3. Pairwise ANI analysis of all studied CPR MAGs in the present study. Table S4. Relative abundance of CPR bacteria in Shatin activated sludge samples. Table S5. Estimated completeness (%) of KEGG modules in the recovered CPR MAGs from Shatin activated sludge. Table S6. The relative abundances of the newly recovered bacterial MAGs in penicillin treated activated sludge metagenome. Table S7. Summary of public CPR bacteria used for pangenomic analysis. Table S8. Carbohydrate-active enzymes frequency in CPR bacteria recovered from activated sludge metagenomes of Shatin WWTP. Table S9. Summary of potential lacterial gene transfer events between CPR bacteria and other prokaryotic organisms (non-CPR bacteria and archaea) in Shatin WWTP. Table S10. Eggnog annotation results of the ORFs on putative horizontal transferred DNA fragments between CPR bacteria and prokaryotic organisms in Shatin WWTP. Table S11. Summary of potential horizontal gene transfer events between CPR bacteria and phages in Shatin WWTP. Table S12. Eggnog annotation results of the ORFs on putative horizontal transferred DNA fragments between CPR bacteria and phages in Shatin WWTP.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 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) | 0.733 | 0.128 |
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".