Photosynthetic parameters in the Beaufort Sea in relation to the phytoplankton community structure
Bibliographic record
Abstract
Abstract. To model phytoplankton primary production from remotely sensed data a method to estimate photosynthetic parameters describing the photosynthetic rates per unit biomass is required. Variability in these parameters must be related to environmental variables that are measurable remotely. In the Arctic, a limited number of measurements of photosynthetic parameter have been carried out with the concurrent environmental variables needed. Therefore, to improve the accuracy of remote estimates of phytoplankton primary production as well as our ability to predict changes in the future such measurements and relationship to environmental variables are required. During the MALINA cruise, a large dataset of these parameters were obtained. Together with previously published datasets, we use environmental and trophic variables to provide functional relationships for these parameters. In particular, we describe several specific aspects: the maximum rate of photosynthesis (Pmaxchl) normalized to chlorophyll decreases with depth and is higher for communities composed of large cells; the saturation parameter (Ek) decreases with depth but is independent of the community structure; and the initial slope of the photosynthesis versus irradiance curve (αchl) normalized to chlorophyll is independent of depth but is higher for communities composed of larger cells. The photosynthetic parameters were not influenced by temperature over the range encountered during the cruise (−2 to 8 °C).
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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 | 0.000 | 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".