Bibliographic record
Abstract
Dinoflagellates are amongst the most abundant and diverse groups of plankton in surface waters and contribute to food web productivity and C:N:P biogeochemistry. Here we analyse the C:N:P of marine, autotrophic, planktonic dinoflagellates compiled from culture data from the scientific literature and test if dinoflagellate C:N:P differs from the Redfield ratio, and whether variability in C:N:P is associated with three traits: cell size, wall structure and toxin production. We find the average C:N:P of dinoflagellates is 90:12:1; higher in C:N, and lower in C:P and N:P than the canonical Redfield ratio. In aggregate the three traits examined here account for between 20–31% while taxonomic order accounts for between 37–38% of the variance in C:N:P. Smaller-sized and thecate taxa are higher in C:N, C:P and N:P than larger-size and athecate taxa. Species known to be able to produce C-rich toxins tend to be higher in C:P and N:P while species known to be able to produce N-rich toxins are lower in C:N, C:P and N:P relative to non-toxic species. These results indicate that any average estimate of dinoflagellate C:N:P will be influenced by the relative number of taxa with these traits.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".