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Record W2899411171 · doi:10.1126/science.aat9072

Composites from renewable and sustainable resources: Challenges and innovations

2018· review· en· W2899411171 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

VenueScience · 2018
Typereview
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSustainabilityPetrochemicalCompatibility (geochemistry)Renewable resourceComposite numberRenewable energyMaterials sciencePlastic wasteEnvironmentally friendlyWaste managementComposite materialEngineering

Abstract

fetched live from OpenAlex

Interest in constructing composite materials from biosourced, recycled materials; waste resources; and their combinations is growing. Biocomposites have attracted the attention of automakers for the design of lightweight parts. Hybrid biocomposites made of petrochemical-based and bioresourced materials have led to technological advances in manufacturing. Greener biocomposites from plant-derived fiber and crop-derived plastics with higher biobased content are continuously being developed. Biodegradable composites have shown potential for major uses in sustainable packaging. Recycled plastic materials originally destined for landfills can be redirected and repurposed for blending in composite applications, thus leading to reduced dependence on virgin petro-based materials. Studies on compatibility of recycled and waste materials with other components in composite structure for improved interface and better mechanical performance pose major scientific challenges. This research holds the promise of advancing a key global sustainability goal.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
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 head0.040
GPT teacher head0.301
Teacher spread0.261 · 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