Tight association between microbial eukaryote and <i>Imitervirales</i> communities in the Pacific Arctic Ocean
Bibliographic record
Abstract
Summary Viruses are important regulatory factors of marine microbial community including microeukaryotes. However, little is known about their role in the northern Chukchi Sea of the Arctic basin, which remains oligotrophic conditions in summer. To elucidate linkages of microbial eukaryotic community with viruses as well as environmental variables, we investigated the community structures of microeukaryotes (3–144 µm and 0.2–3 µm size fractions) and Imitervirales (0.2–3 µm size fraction), a major group of viruses infecting marine microeukaryotes. Surface water samples were collected at 21 ocean stations located in the northeastern Chukchi Sea (NECS), an adjacent area outside the Beaufort Gyre (Adjacent Sea; AS), and two melt ponds on sea ice in the summer of 2018. At the ocean stations, nutrient concentrations were low in most of the locations expect at the shelf in the AS. The community variations were significantly correlated between eukaryotes and Imitervirales , even within the NECS characterized by relatively homogeneous environmental conditions. The association of the eukaryotic community with the viral community was stronger than that with geographical and physicochemical environmental factors. These results suggest that Imitervirales are actively infecting their hosts even in cold and oligotrophic sea water in the Arctic Ocean.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".