MétaCan
Menu
Back to cohort
Record W3206585717 · doi:10.3390/en14206792

Recent Advances in Cellulose Nanofibers Preparation through Energy-Efficient Approaches: A Review

2021· review· en· W3206585717 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

VenueEnergies · 2021
Typereview
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of CalgaryUniversity of AlbertaLakehead UniversityUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsRaw materialRenewable energyProduction costProduction (economics)NanofiberRenewable resourceCelluloseProcess engineeringBiochemical engineeringNanotechnologyMaterials scienceEngineeringChemistryMechanical engineeringChemical engineering

Abstract

fetched live from OpenAlex

Cellulose nanofibers (CNFs) and their applications have recently gained significant attention due to the attractive and unique combination of their properties including excellent mechanical properties, surface chemistry, biocompatibility, and most importantly, their abundance from sustainable and renewable resources. Although there are some commercial production plants, mostly in developed countries, the optimum CNF production is still restricted due to the expensive initial investment, high mechanical energy demand, and high relevant production cost. This paper discusses the development of the current trend and most applied methods to introduce energy-efficient approaches for the preparation of CNFs. The production of cost-effective CNFs represents a critical step for introducing bio-based materials to industrial markets and provides a platform for the development of novel high value applications. The key factor remains within the process and feedstock optimization of the production conditions to achieve high yields and quality with consistent production aimed at cost effective CNFs from different feedstock.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.094
GPT teacher head0.375
Teacher spread0.281 · 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