Diversity of algal viruses in various North American freshwater environments
Bibliographic record
Abstract
To examine algal virus (Phycodnaviridae) genetic diversity in freshwater environments, gene fragments were cloned and sequenced from a river and a reservoir in Colorado, USA, and 2 different lakes in Ontario, Canada using PCR methods that target a diverse subset of known Phycodnaviridae DNA polymerase genes. Numerous phycodnavirus gene sequences were obtained from every sample, and rarefaction analysis of the sequence libraries demonstrated that virus richness was variable among different sample locations, and among samples collected from the same location at different times. Phylogenetic analysis of the unique sequences from each sample indicated that most sequences from the same geographic region (i.e. Colorado or Ontario) clustered together, but several exceptions were also observed. Phylogenetic analysis also demonstrated that the sequences obtained were more closely related to sequences from cultivated marine phycodnaviruses belonging to the genus Prasinovirus than to those from cultivated freshwater phycodnaviruses from the genus Chlorovirus. Overall, phycodnavirus sequences originating from cultivated marine viruses and marine clone libraries were not genetically distinct from the freshwater phycodnavirus sequences reported in this study.
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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 | 0.000 |
| 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) | 0.000 | 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".