Additional file 1 of Lower viral evolutionary pressure under stable versus fluctuating conditions in subzero Arctic brines
Bibliographic record
Abstract
Additional file 1: Table S1. Viromic statistics and viral concentrations of four samples. Table S2. Comparison in virus recovery from short- and long-read assemblies. Table S3. Size summary of vOTUs from CB17. The two assembly types (i.e., short+long-read assembly and short-read-only assesmbly) had identical sequencing depth, as described in Table S2. Table S4. Size summary of vOTUs from CB18. The two assembly types (i.e., short+long-read assembly and short-read-only assesmbly) had identical sequencing depth, as described in Table S2. Table S5. Taxonomic assignments and viral cluster summary. Viruses from this study, the NCBI RefSeq database, and 250 environmental metagenomes were included for clustering analysis. The environmental metagenomes included samples from below ecosystems: global oceans (GOV2 dataset), deep ocean water, deep ocean sediment, surfacer layer (top 1 meter) of permafrost (IsoGenie), soil, air, glacier cryoconite, glacier ice core, and lake water. Table S6. Viral cluster summary of the two vOTUs encoding fatty acid desaturase (FAD) genes. The two vOTUs are vOTU105_CB18_230153 and vOTU43_CB18_222366. Viral contigs that connected to above two vOTUs from Figure S4 and Table S5 were used for network analysis in this Table. Table S7. Putative gene annotations of the 11,088 vOTUs from this study. Genes were annotated by comparing them to three databases PFAM, KEGG, and Uniref using DRAMv. Table S8. Gene annotation and phage gene identification of the vOTU vOTU4_CB17_43158 encoding the AMG espG.The methods used for gene annotation and phage gene identification are described in the legend of Fig. 5. Table S9. Tests for selection pressure of epsG gene using site and free-ratio models. Table S10. Summay and annotations of all brine viral genes under positive selection. The 23 putative phage tail fiber genes were highlighted in grey (i.e., Rows 3-25). Table S11. Scripts used for quality control of the short-read viromes based on DOE Joint Genome Institute's standards pipeline (Clum et al., 2021).
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.844 | 0.157 |
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".