The macromolecular composition of noncalcified marine macroalgae
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The macromolecular composition of macroalgae influences nutrient flow and food quality in aquatic ecosystems and the value of macroalgae species for human consumption, aquaculture, biofuels, and other applications. We used literature data (125 publications, 1,117 observations) and a hierarchal Bayesian statistical model to estimate the average macromolecular composition, protein, lipid, and carbohydrate of macroalgae as a whole and at the phylum level. Our focus was on marine, noncalcified macroalgae sampled from wild-grown populations in the field. We found that the median macromolecular composition is 9.98% protein, 2.7% lipid, 48.5% carbohydrate, and 31.8% ash as percent dry weight. We compared the median macromolecular content of macroalgae to microalgae and herbaceous plants and test for differences in macromolecular content across macroalgal phyla. Macroalgae were much more enriched in carbohydrate and minerals than the microalgae and lower in protein and lipid than many herbaceous plants. Rhodophyte macroalgae have significantly less lipid and more protein and the Ochrophyte macroalgae have significantly less protein than the average.
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.
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) | 0.001 | 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 it