MétaCan
Menu
Back to cohort

On the New RILEM Technical Committee TC APD: Alternative Paving Materials – Design and Performance

2025· article· en· W4406664748 on OpenAlexaff
Augusto Cannone Falchetto, Fan Yin, Maria Chiara Cavalli, Salvatore Mangiafico, Krishna Prapoorna Biligiri, Justine Cantot, Punyaslok Rath, Avishreshth Singh, Michael Elwardany, Di Wang, Chen Chen, James Grenfell, Fan Zhang, Yuxuan Sun, Каteryna Krayushkina

Bibliographic record

VenueRILEM Technical Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEngineeringForensic engineering

Abstract

fetched live from OpenAlex

This paper introduces the new RILEM Technical Committee on Alternative Paving Materials – Design and Performance (TC APD), which builds upon the foundational efforts of the former TC 279-WMR focused on the Valorisation of Waste and Secondary Materials for Roads. The TC APD aims to advance the understanding of alternative paving materials, emphasizing their design and performance as essential components of road composites. The committee addresses three areas of investigation, each dedicated to examining the current technological state of the art, the design process and the field performance of composites incorporating alternative paving materials. The manuscript provides a comprehensive overview of the TC's background, outlines the research objectives and activities proposed, and discusses the committee's position within RILEM and the broader research community. Additionally, it details the anticipated outcomes and the potential impact of the committee's work on advancing the field of sustainable road construction.

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)0.018
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0100.003
Open science0.0040.004
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0210.022

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 head0.217
Teacher spread0.207 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueRILEM Technical LettersSame topicNuclear and radioactivity studiesFrench-language works237,207