Phylogenetic Diversity in the Macromolecular Composition of Microalgae
Bibliographic record
Abstract
The elemental stoichiometry of microalgae reflects their underlying macromolecular composition and influences competitive interactions among species and their role in the food web and biogeochemistry. Here we provide a new estimate of the macromolecular composition of microalgae using a hierarchical Bayesian analysis of data compiled from the literature. The median macromolecular composition of nutrient-sufficient exponentially growing microalgae is 32.2% protein, 17.3% lipid, 15.0% carbohydrate, 17.3% ash, 5.7% RNA, 1.1% chlorophyll-a and 1.0% DNA as percent dry weight. Our analysis identifies significant phylogenetic differences in macromolecular composition undetected by previous studies due to small sample sizes and the large inherent variability in macromolecular pools. The phylogenetic differences in macromolecular composition lead to variations in carbon-to-nitrogen ratios that are consistent with independent observations. These phylogenetic differences in macromolecular and elemental composition reflect adaptations in cellular architecture and biochemistry; specifically in the cell wall, the light harvesting apparatus, and storage pools.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".