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Record W2073469040 · doi:10.1021/bm025576q

NMR Imaging of High-Amylose Starch Tablets. 2. Effect of Tablet Size

2002· article· en· W2073469040 on OpenAlexaff
Cédric Malveau, Wilms E. Baille, R. H. Marchessault

Bibliographic record

VenueBiomacromolecules · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsSwellingAmylosePenetration (warfare)StarchPolymerSwelling capacityChemistryGravimetric analysisMaterials scienceChemical engineeringPolymer chemistryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Carbohydrate polymers are widely used for pharmaceutical applications such as the controlled release of drugs. The swelling and water mobility in high-amylose starch tablets are important parameters to be determined for these applications. They have been studied at different time intervals by nuclear magnetic resonance imaging (NMRI) after the immersion of the samples in water. These tablets have a hydrophilic matrix, which swells anisotropically and forms a hydrogel in water. NMRI shows clearly the anisotropy of the water penetration and the swelling along the radial and axial dimensions of the tablets. Empirical relationships are established to describe the kinetics of water penetration and swelling of the tablets. Results show that water uptake and tablet swelling strongly depend on the size of the tablets. Gravimetric measurements of water uptake were also performed in comparison with the NMRI results.

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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.000
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 head0.005
GPT teacher head0.274
Teacher spread0.269 · 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

Citations31
Published2002
Admission routes1
Has abstractyes

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