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Record W3099711033 · doi:10.1080/14686996.2020.1848213

Recent progress in the conversion of biomass wastes into functional materials for value-added applications

2020· article· en· W3099711033 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

VenueScience and Technology of Advanced Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiomass (ecology)ReuseRaw materialWaste managementEnvironmental scienceValue addedEngineeringChemistry

Abstract

fetched live from OpenAlex

The amount of biomass wastes is rapidly increasing, which leads to numerous disposal problems and governance issues. Thus, the recycling and reuse of biomass wastes into value-added applications have attracted more and more attention. This paper reviews the research on biomass waste utilization and biomass wastes derived functional materials in last five years. The recent research interests mainly focus on the following three aspects: (1) extraction of natural polymers from biomass wastes, (2) reuse of biomass wastes, and (3) preparation of carbon-based materials as novel adsorbents, catalyst carriers, electrode materials, and functional composites. Various biomass wastes have been collected from agricultural and forestry wastes, animal wastes, industrial wastes and municipal solid wastes as raw materials with low cost; however, future studies are required to evaluate the quality and safety of biomass wastes derived products and develop highly feasible and cost-effective methods for the conversion of biomass wastes to enable the industrial scale production.

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 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 score0.003
Threshold uncertainty score0.200

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 studies0.0000.001
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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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