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Record W3160404135 · doi:10.1039/d0nh00696c

Chitin and chitosan on the nanoscale

2021· review· en· W3160404135 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanoscale Horizons · 2021
Typereview
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsNational Research Council CanadaMcGill UniversityCentre in Green Chemistry and Catalysis
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsChitinNanocelluloseChitosanNanotechnologyNanoscopic scaleFabricationMaterials sciencePolymer scienceChemistryCelluloseOrganic chemistry

Abstract

fetched live from OpenAlex

In a matter of decades, nanomaterials from biomass, exemplified by nanocellulose, have rapidly transitioned from once being a subject of curiosity to an area of fervent research and development, now reaching the stages of commercialization and industrial relevance. Nanoscale chitin and chitosan, on the other hand, have only recently begun to raise interest. Attractive features such as excellent biocompatibility, antibacterial activity, immunogenicity, as well as the tuneable handles of their acetylamide (chitin) or primary amino (chitosan) functionalities indeed display promise in areas such as biomedical devices, catalysis, therapeutics, and more. Herein, we review recent progress in the fabrication and development of these bio-nanomaterials, describe in detail their properties, and discuss the initial successes in their applications. Comparisons are made to the dominant nanocelluose to highlight some of the inherent advantages that nanochitin and nanochitosan may possess in similar application.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.052
GPT teacher head0.339
Teacher spread0.287 · 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