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Record W1648701727 · doi:10.1061/9780784479315.017

Albedo of Pavement Surfacing Materials: In Situ Measurements

2015· article· en· W1648701727 on OpenAlexafffundabout
Caroline Richard, Guy Doré, Chantal Lemieux, Jean-Pascal Bilodeau, Jade Haure-Touzé

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlbedo (alchemy)Environmental scienceDurabilityPermafrostGeologyGeotechnical engineeringHydrology (agriculture)Atmospheric sciencesMaterials scienceComposite material

Abstract

fetched live from OpenAlex

In order to limit heat intake in the ground underneath pavements, high albedo surfaces can be used in cold regions to mitigate permafrost degradation. In this study, experimental sections at Site Experimental Routier de l’Université Laval (Québec, 2014), on the Alaska Highway (Beaver Creek, Yukon, 2012 and 2014 and at km post 1786, Yukon, 2014), and in Tasiujaq (Nunavik, Québec, 2015) were used to document the effectiveness and durability of high albedo surfacing materials. The test sections were equipped with thermistors and data loggers recording surface temperatures. Albedo and skid resistance were also monitored at these sections. In addition to the experimental sites, several albedo measurements were made on asphalt surfaces to develop a relationship between albedo and pavement age.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.049
GPT teacher head0.244
Teacher spread0.195 · 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 designBench or experimental
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

Citations29
Published2015
Admission routes3
Has abstractyes

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