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Record W2077023384 · doi:10.1021/bm7011696

Solution Properties of Conventional Gum Arabic and a Matured Gum Arabic (<i>Acacia</i> (sen) SUPER GUM)

2008· article· en· W2077023384 on OpenAlexaff
Qi Wang, Walther Burchard, Steve W. Cui, Xiaoqing Huang, Glyn O. Phillips

Bibliographic record

VenueBiomacromolecules · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRadius of gyrationMolar massGum arabicChemistryNatural gumExponentStatic light scatteringPolymerSolventAnalytical Chemistry (journal)Dynamic light scatteringChromatographyMaterials scienceOrganic chemistryPolysaccharideNanotechnology

Abstract

fetched live from OpenAlex

Dilute solution properties of two specially matured gum arabic samples (EM1 and EM2) were compared to the conventional gum (EM0) using static light scattering. The apparent molar mass (M(w,app) and radius of gyration (R(g,app)) for the three samples showed unusual concentration dependence. These data were satisfactorily interpreted by a simple association model that takes into account the repulsive interaction among clusters, which allowed us to obtain the true molar mass (Mw(0)) and radius of gyration (Rg(0)). A common power law relation was observed between Mw(0) and Rg(0) , giving a somewhat higher exponent than expected for linear and branched polymers in a good solvent. Mw(0) and Rg(0) obtained for the three gums do not differ significantly from each other. However, the data showed clearly a constant increase of the association from EM0 to EM2 with increasing concentration. This is in accordance with the previously observed improved functional properties for the matured products.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.194
Teacher spread0.166 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations35
Published2008
Admission routes1
Has abstractyes

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