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Record W2952464697 · doi:10.1089/ind.2019.29172.qyh

Growing the Bioeconomy: Advances in the Development of Applications for Cellulose Filaments and Nanocrystals

2019· article· en· W2952464697 on OpenAlex
Wadood Y. Hamad, Chuanwei Miao, Stephanie Beck

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

VenueIndustrial Biotechnology · 2019
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsFPInnovationsCanadian Forest Service
FundersNatural Resources Canada
KeywordsNanotechnologyInvestment (military)Resource (disambiguation)BusinessMultitudeRenewable resourceRenewable energyCelluloseMaterials scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

Forestry-based products have long capitalized on the ability of lignocellulosic materials to form fibers, and new forestry-based functional materials have the potential to compete with other materials not only based on performance, as indicated by the scientific evidence, but also on merits of recyclability and being a renewable resource. In addition to cost-effectiveness and product differentiation, the forestry industry is considering new technologies to healthily grow and secure long-term, respectable return on investment. This brief review offers a sense of the technological advances that have been made in the field of nanomaterials, with a vision to developing functional forestry-based materials that could find enhanced applications in a multitude of industries, for instance, intelligent packaging, cosmetics, paints and coatings, foods, and advanced electronic and photonic materials, to name a few examples.

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 categoriesnone
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 score0.188
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.302
Teacher spread0.265 · 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