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Record W4387671491 · doi:10.3390/su152014892

Life Cycle Assessment of Road Pavements That Incorporate Waste Reuse: A Systematic Review and Guidelines Proposal

2023· review· en· W4387671491 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

VenueSustainability · 2023
Typereview
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersFundação de Amparo à Pesquisa e Inovação do Espírito Santo
KeywordsLife-cycle assessmentReuseScope (computer science)Context (archaeology)GuidelineEngineeringSustainabilityEnvironmental impact assessmentEnvironmental planningWaste managementConstruction engineeringEnvironmental scienceComputer scienceProduction (economics)

Abstract

fetched live from OpenAlex

Life cycle assessment (LCA) is a methodology that has been widely used to evaluate the environmental impact of products and processes throughout entire life cycles. In this context, the reuse of waste in paved road construction is a practice that has received increasing attention as a sustainable alternative to solid waste disposal. This article presents a systematic review of existing studies on the LCA of paved roads that incorporate waste reuse and proposes a guideline for LCA in this context. Several criteria were analyzed in the articles, and the results showed that only 5% of the articles followed all the recommendations set out in ISO 14040. The proposed guideline aims to provide guidance for future research and includes recommendations for each of the steps involved in LCA, from defining the objectives and scope of the study to interpreting the results.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.048
GPT teacher head0.362
Teacher spread0.314 · 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