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Record W2753726964 · doi:10.1039/c7nr04994c

Nanocellulose as a sustainable biomass material: structure, properties, present status and future prospects in biomedical applications

2017· review· en· W2753726964 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 · 2017
Typereview
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of FrederictonUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsNanocelluloseBiomass (ecology)NanotechnologyMaterials scienceBiochemical engineeringEnvironmental scienceEngineeringChemical engineeringCelluloseBiologyEcology

Abstract

fetched live from OpenAlex

Nanocellulose, extracted from the most abundant biomass material cellulose, has proved to be an environmentally friendly material with excellent mechanical performance owing to its unique nano-scaled structure, and has been used in a variety of applications as engineering and functional materials. The great biocompatibility and biodegradability, in particular, render nanocellulose promising in biomedical applications. In this review, the structure, treatment technology and properties of three different nanocellulose categories, i.e., nanofibrillated cellulose (NFC), nanocrystalline cellulose (NCC) and bacterial nanocellulose (BNC), are introduced and compared. The cytotoxicity, biocompatibility and frontier applications in biomedicine of the three nanocellulose categories were the focus and are detailed in each section. Future prospects concerning the cytotoxicity, applications and industrial production of nanocellulose are also discussed in the last section.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.035
GPT teacher head0.338
Teacher spread0.303 · 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