Low viral predation pressure in cold hypersaline <scp>A</scp> rctic sediments and limits on lytic replication
Bibliographic record
Abstract
Viruses are ubiquitous drivers of microbial ecology and evolution and contribute to biogeochemical cycling. Attention to these attributes has been more substantial for marine viruses than viruses of other environments. Microscopy-based investigation of the viral communities from two cold, hypersaline Arctic springs was undertaken to explore the effects of these conditions on microbe-viral ecology. Sediments and water samples were collected along transects from each spring, from anoxic spring outlets through oxygenated downstream channels. Viral abundance, virus-microbe ratios and modelled virus-microbe contact rates were lower than comparable aqueous and sedimentary environments and most similar to deep subsurface sediments. No individual cell from either spring was visibly infected. Viruses in these springs appear to play a smaller role in controlling microbial populations through lytic activity than in marine water column or surface sedimentary environments. Relief from viral predation indicates the microbial communities are primarily controlled by nutrient limitation. The similarity of these springs to deep subsurface sediments suggests a biogeographic divide in viral replication strategy in marine sediments.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".