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Record W4242103697 · doi:10.1021/bk-2006-0934.ch011

Characterization of Glycol Chitosan: A Potential Material for Use in Biomedical and Pharmaceutical Applications

2006· book-chapter· en· W4242103697 on OpenAlexaff
Darryl K. Knight, Stephen N. Shapka, Brian G. Amsden

Bibliographic record

VenueACS symposium series · 2006
Typebook-chapter
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsQueen's University
Fundersnot available
KeywordsChitosanChemistryEthylene glycolPotassium persulfateAmine gas treatingFractionationPEG ratioNuclear chemistryOrganic chemistryPolymerization

Abstract

fetched live from OpenAlex

Glycol chitosan, a water soluble chitosan derivative being proposed as a material for pharmaceutical and biomedical engineering applications, was modified to further promote its use in vivo . Initial characterization of the glycol chitosan with 1 H NMR spectroscopy illustrated the presence of both secondary and tertiary amine groups. Fractionation of glycol chitosan with nitrous acid resulted in a significant reduction in the number average molecular weight, specifically, from 210 to approximately 7-8 kDa. However, the structural integrity of the glycol chitosan was lost following fractionation, as the secondary amine groups were converted to N-nitrosamines, which are potentially carcinogenic. An increase in the pH of the reaction limited their formation, but not entirely; therefore, a second approach to reducing the molecular weight was sought. The free radical degradation, initiated with potassium persulfate, was not as effective at reducing the molecular weight, which ranged from 17 to 20 kDa post fractionation, but did retain the structural integrity of the glycol chitosan.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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