Phytoplankton antioxidant systems and their contributions to cellular elemental stoichiometry
Bibliographic record
Abstract
Abstract Oxidative stress plays a role in many aspects of cellular metabolism, and as a result, antioxidants have the potential to impact cellular stoichiometry and biogeochemical cycles. We reviewed how antioxidant systems influence macronutrient and micronutrient stoichiometry in marine phytoplankton and identified that antioxidant systems have important implications for micronutrient stoichiometry. By leveraging diatom proteomic data, we empirically estimated the level of micronutrient quota variation that can be attributed to antioxidant systems. Fe‐containing antioxidant expression may contribute to 3.3–10 μ mol : mol variation in Fe : C, and superoxide dismutases appear to be important contributors to variation in Mn, Ni, Zn, and Cu quotas in phytoplankton. Critical next steps for the study of phytoplankton antioxidant systems are to (1) distinguish between oxidative stress and redox‐based gene regulation and (2) determine how antioxidants influence variation or consistency in micronutrient quotas under various environmental conditions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".