MétaCan
Menu
Back to cohort
Record W4366502801 · doi:10.11159/iceptp23.148

Valorization of Plastic and Cork Wastes in the Production of New Composite Materials

2023· article· en· W4366502801 on OpenAlexvenueno aff
Svetlana Petlitckaia, Toussaint Barboni, Paul‐Antoine Santoni

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
Fundersnot available
KeywordsCorkComposite numberProduction (economics)Waste managementMaterials scienceEnvironmental sciencePulp and paper industryComposite materialProcess engineeringEngineering

Abstract

fetched live from OpenAlex

Plastics is a revolutionary material widespread in everyday life However, it is important to find the new way to recycle and reuse this plastic because there are about 5-13 million tons of plastic end up in the ocean. Pollution caused by plastics damages of the environment, human health and economy of different countries. The plastic waste management is the global problem. The large volume plastics requires strategies to improve the valorization of the waste generated after consumption in order to minimize impacts The several works have been shown that the use of recycled polymer for composites production can be a feasible alternative from an economical and environmental point of view The use of the waste materials as filler and as a matrix for the composite materials is receiving increasing attention as an approach to increasing the economic value of streams.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.185
Teacher spread0.178 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicInnovations in Concrete and Construction MaterialsFrench-language works237,207