Seasonal and Form-Specific Gene Expression Signatures Uncover Different Generational Strategies of the Pelagic Tunicate Salpa thompsoni During the Southern Ocean Winter
Bibliographic record
Abstract
The pelagic tunicateSalpa thompsoniis recognized as a major metazoan grazer in the Southern Ocean. Long term observations show an increase in this species’ biomass and a southward shift in its distribution both of which are positively correlated with ocean warming and winter sea ice decline around the Antarctic Peninsula. However, our understanding on how salps adapt their life cycle to the extreme seasonality of the Southern Ocean and the putative differences between its two reproductive forms (aggregates, solitaries) is rudimentary. In particular, our current knowledge of whether and howS. thompsonioverwinter is limited, largely due to winter sampling constraints. In this study, we investigated the form-specific gene expression profiles ofSalpa thompsoniduring the austral autumn and winter. Between the seasons, genes related to translation showed the biggest difference in gene expression. We found more genes were upregulated in solitaries compared to aggregates, indicating a potentially form-specific overwintering strategy. Our data provide first insights into the seasonal and form-specific physiology of salps by considering their complex life cycle, thereby contributing to a more comprehensive understanding of the response of salps to seasonal changes in their environment and to anthropogenic induced global climate change.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".