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Record W2141032591 · doi:10.1155/2013/508540

Fragmentation of Chitosan by Acids

2013· article· en· W2141032591 on OpenAlex
Mohammad Reza Kasaai, Joseph Arul, Gérard Charlet

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.

Bibliographic record

VenueThe Scientific World JOURNAL · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDispersityChitosanChemistryHydrochloric acidFragmentation (computing)Aqueous solutionSize-exclusion chromatographyKineticsGel permeation chromatographyViscometerChromatographyPolymer chemistryNuclear chemistryOrganic chemistryMaterials sciencePolymerViscosity

Abstract

fetched live from OpenAlex

Fragmentation of chitosan in aqueous solution by hydrochloric acid was investigated. The kinetics of fragmentation, the number of chain scissions, and polydispersity of the fragments were followed by viscometry and size exclusion chromatography. The chemical structure and the degree of N-acetylation (DA) of the original chitosan and its fragments were examined by (1)H NMR spectroscopy and elemental analysis. The kinetic data indicates that the reaction was of first order. The results of polydispersity and the DA suggest that the selected experimental conditions (temperature and concentration of acid) were appropriate to obtain the fragments having the polydispersity and the DA similar to or slightly different from those of the original one. A procedure to estimate molecular weight of fragments as well as the number of chain scissions of the fragments under the experimental conditions was also proposed.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.007
GPT teacher head0.228
Teacher spread0.220 · 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