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Record W4403243540 · doi:10.3390/md22100464

Characterization of Unfractionated Polysaccharides in Brown Seaweed by Methylation-GC-MS-Based Linkage Analysis

2024· article· en· W4403243540 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMarine Drugs · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeaweed-derived Bioactive Compounds
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsFucoseGlycosidic bondPolysaccharideCelluloseChemistryGalactanUronic acidMonosaccharideHydrolysisGlycanAcid hydrolysisChromatographyBiochemistryGalactoseEnzymeGlycoprotein

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.229
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it