Characterization of Unfractionated Polysaccharides in Brown Seaweed by Methylation-GC-MS-Based Linkage Analysis
Bibliographic record
Abstract
This study introduces a novel approach to analyze glycosidic linkages in unfractionated polysaccharides from alcohol-insoluble residues (AIRs) of five brown seaweed species. GC-MS analysis of partially methylated alditol acetates (PMAAs) enables monitoring and comparison of structural variations across different species, harvest years, and tissues with and without blanching treatments. The method detects a wide array of fucose linkages, highlighting the structural diversity in glycosidic linkages and sulfation position in fucose-containing sulfated polysaccharides. Additionally, this technique enhances cellulose quantitation, overcoming the limitations of traditional monosaccharide composition analysis that typically underestimates cellulose abundance due to incomplete hydrolysis of crystalline cellulose. The introduction of a weak methanolysis-sodium borodeuteride reduction pretreatment allows for the detection and quantitation of uronic acid linkages in alginates.
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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 | 0.001 | 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".