Seawater carbonate chemistry and oxidative stress response, carbon metabolism and rapid light curve fitted parameters of phytoplankton Phaeodactylum tricornutum
Bibliographic record
Abstract
We conducted a full-factorial lab experiment to study the individual and combined effects of temperature (18°C and 21°C), pCO2 (400 and 1000 ppm), and dissolved N:P ratio (16 and 25 molar) on the antioxidant capacity and carbon metabolism of the phytoplankton Phaeodactylum tricornutum (strain CCAP 1052/1A). The antioxidant response was assessed based on different biomarkers, including the contents of protective carotenoids (ß-Carotene, diadinoxanthin and violaxanthin), and by determination of antioxidant enzyme activities, and Malondialdehyde (MDA) as a biomarker for oxidative stress. We quantified the activity of Managanese Superoxide Dismutase (SOD-Mn), Glutathione S-transferase (GST), Catalase (CAT), Glutathione Peroxidase (GPx). As possible consequence of oxidative stress on metabolic pathways of carbon, we also quantified carbon fluxes by measuring rates of growth, respiration, dissolved organic carbon (DOC) exudation, and cellular organic carbon content and particulate phosphorus (PP). We also quantified the concentration of photosynthetic pigments chlorophyll a (Chl-a) and fucoxanthin. We used least-squares fitting on the obtained data to derive physiological photosynthesis parameters, such as compensation point, as well as photochemical efficiency (α), light acclimation index (Ik) and maximum net photosynthesis rate (Vmax).
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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".