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Record W4248114822 · doi:10.26434/chemrxiv.7312070

Synthesis of High Molecular Weight Chitosan from Chitin by Mechanochemistry and Aging

2018· preprint· en· W4248114822 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.

Bibliographic record

VenueChemRxiv · 2018
Typepreprint
Languageen
FieldEngineering
TopicDyeing and Modifying Textile Fibers
Canadian institutionsMcGill University
Fundersnot available
KeywordsChitinChitosanDepolymerizationMagic angle spinningChemistryChemical engineeringSolventAcetylationPolymer chemistryOrganic chemistryMaterials scienceBiochemistryNuclear magnetic resonance spectroscopyEngineering

Abstract

fetched live from OpenAlex

Chitosan can be obtained from the deacetylation of chitin. This process is however difficult and usually accompanied by depolymerization, affording low molecular weight chitosan. We report a novel path, relying on a combination of mechanochemitry and aging, to afford high molecular weight chitosan with minimal use of energy and solvent. This method is versatile and applicable to a number of chitin sources, including crude crustaceans and insect shells, yielding deacetylation up to 98% and remarkably high molecular weights. Chitin deacetylation was measured by magic angle spinning nuclear magnetic resonance and molecular weight by viscometry. This process affords chitosan in a safer fashion and with less materials and energy usage than the classic hydrothermal one.

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 categoriesMeta-epidemiology (narrow)
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.186
Teacher spread0.181 · 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