MétaCan
Menu
Back to cohort
Record W4382722014 · doi:10.4236/sgre.2023.146007

Waste Recovery and Sustainable Development. A Case Study of Material Development from Used Tires in Africa

2023· article· en· W4382722014 on OpenAlexfundno aff
Bachirou Bogno, Paul-Salomon Ngohe Ekam, Sali Mohammadou, Dieudonné Kidmo Kaoga, Abderrezak Guenounou, Michel Aillerie

Bibliographic record

VenueSmart Grid and Renewable Energy · 2023
Typearticle
Languageen
FieldComputer Science
TopicEnvironmental Engineering and Cultural Studies
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsVulcanizationSustainable developmentNatural rubberCrusherWork (physics)Process (computing)Materials scienceWaste managementProcess engineeringManufacturing engineeringEngineeringMechanical engineeringComposite materialComputer science

Abstract

fetched live from OpenAlex

This paper outlines a mechanical transformation process for rubber recycling, demonstrating the development of a new material from used tires. With the crumbs obtained using a crusher-compactor, a novel material for the manufacture of O-rings has been developed, with properties close to those found on the market. The process includes an experimental methodology of a sulfur vulcanization system choice and the quantification of ingredients, as well as the experimental determination of cure parameters. Mechanical tests on the samples completed the work by providing the mechanical characteristics of both unaged and aged (thermo-oxidative ageing) novel material. This process has a high potential for sustainable development and industrialization, making it a valuable contribution to the recycling of rubber in African developing countries.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.179
Teacher spread0.168 · 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 designObservational
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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueSmart Grid and Renewable EnergySame topicEnvironmental Engineering and Cultural StudiesFrench-language works237,207