Temporal dynamics and structure of picocyanobacteria and cyanomyoviruses in two large and deep peri-alpine lakes
Bibliographic record
Abstract
We conducted a 1-year survey of the surface waters of two deep peri-alpine lakes, and investigated the abundances and community structure of picocyanobacteria and co-occurring cyanomyophages. Picocyanobacterial abundances ranged between 4.5 × 10(4) and 1.6 × 10(5) cells mL(-1) in Lake Annecy vs. 2.2 × 10(3) and 1.6 × 10(5) cells mL(-1) in Lake Bourget. Cyanomyoviruses ranged between 2.8 × 10(3) and 3.7 × 10(5) copies of g 20 mL(-1) in Lake Annecy vs. between 9.4 × 10(3) and 9.4 × 10(5) copies of g 20 mL(-1) in Lake Bourget. The structures of picocyanobacteria and cyanomyoviruses differed in the two lakes, and a more pronounced dynamic pattern with greater seasonality was observed in Lake Bourget. At the annual scale, there was no relationship between cyanomyovirus and picocyanobacterial abundances or structures, but we could observe that abundances of the two communities covaried in spring in Lake Bourget. We showed that (i) the changes of picocyanobacteria and cyanomyoviruses were caused by the combined effect of several environmental and biological factors the importance of which differed over time and between the lakes, and (ii) the viral control of the picocyanobacterial community was probably relatively weak at the scale of the investigation.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".