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Record W2073867189 · doi:10.5539/mas.v7n11p1

Environmental Impact Assessment of Road Asphalt Pavements

2013· article· en· W2073867189 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2013
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental impact assessmentWork (physics)Life-cycle assessmentTransport engineeringProduction (economics)Computer scienceAsphaltOrder (exchange)Call for bidsRoad constructionEnvironmental economicsCivil engineeringEnvironmental resource managementEnvironmental scienceEngineeringBusinessEconomics

Abstract

fetched live from OpenAlex

This paper deals with a versatile, synthetic, simple and user-friendly method based on Life Cycle Assessment studies which summarizes multifaceted, often competing, environmental, technical and economic aspects in road construction. In many cases just economic criteria are applied in call for tenders, because the calculation of the environmental impact of road construction is difficult. In fact, it can be referred to many available options and both the economic and the environmental suitabilities have to be considered, in order to achieve globally sustainable results about road infrastructure work. In this research, the weighted sum model of multicriteria analysis is identified as the tool to evaluate global impact of road works, to compare solutions and to choose the best one. The advantages of the proposed approach are that the local contest and the stakeholders’ objective are represented by adopting variable parameters and weights, in order to apply the method to several contexts. A case study explains potential environmental implications of using this new Road Environmental Impact Assessment to calculate effect related to the production of asphalt pavement, considering the production system for aggregates from cradle to gate, the materials transportation to road site and the works to have the road done.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.267
Teacher spread0.255 · 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