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Record W591483356

Sustainability Metrics of Two Pavement Rating Systems Developed in Canada

2014· article· fr· W591483356 on OpenAlexaboutno aff
T Kazmierowski, Mary Beth Navarra

Bibliographic record

VenueTransportation 2014: Past, Present, Future - 2014 Conference and Exhibition of the Transportation Association of Canada // Transport 2014 : Du passé vers l'avenir - 2014 Congrès et Exposition de 'Association des transports du Canada · 2014
Typearticle
Languagefr
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityRating systemChristian ministryBest practiceLife-cycle assessmentEngineeringUnit (ring theory)Transport engineeringPoint (geometry)Construction engineeringArchitectural engineeringComputer scienceEnvironmental economicsManagement
DOInot available

Abstract

fetched live from OpenAlex

Sustainability is an increasingly important consideration in road building across North America. Pavement sustainability can be evaluated using several different methods or tools, including life cycle assessment, life cycle cost analysis, performance assessment, and sustainability rating systems (SRS). A SRS is basically a list of sustainability best practices with a related measure, usually a point score, which quantifies each best practice in a common unit. In an effort to bring awareness of and promote “green” initiatives to designers, both the Ontario Ministry of Transportation (MTO) and Golder Associates created user-friendly SRS to promote sustainable pavement technologies for the design, construction, rehabilitation, reconstruction, and preservation of roads. The MTO system is known as GreenPave and the Golder system as GoldSET. This paper describes the development and implementation of these two SRS and compares their analysis through two case studies, one dealing with a rigid pavement rehabilitation project and the other addresses a flexible pavement project.

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)0.004
metaresearch head score (Gemma)0.016
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 score0.050
Threshold uncertainty score0.360

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.012
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueTransportation 2014: Past, Present, Future - 2014 Conference and Exhibition of the Transportation Association of Canada // Transport 2014 : Du passé vers l'avenir - 2014 Congrès et Exposition de 'Association des transports du CanadaSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207