MétaCan
Menu
Back to cohort
Record W1990817142 · doi:10.1061/41072(359)33

Introduction to Cold Regions Pavement Engineering

2009· article· en· W1990817142 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversité Laval
FundersUniversity of Alaska Anchorage
KeywordsPermafrostSnowCold climateCivil engineeringEngineeringPopulationTransport engineeringForensic engineeringConstruction engineeringComputer scienceGeologyGeographyMeteorology

Abstract

fetched live from OpenAlex

Cold Regions Pavement Engineering book by Guy Doré and Hannele Zubeck was recently published by the ASCE Press and McGraw-Hill. It prepares engineers to make right decisions in areas, where freezing temperatures, snow and ice, unstable soils, sparse population, long road mileage and often limited funds dictate design and maintenance actions on pavement structures. The book aimed to practicing Civil Engineers covers the unique environment, performance challenges, testing, design, management and rehabilitation of cold regions pavements including permafrost areas. Combining the latest research and proved techniques from the Northern United States, Canada and the Northern Europe, this is the first complete reference for all pavement projects in cold regions. This invited paper introduces the reader to the issues presented in the book.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.183
Teacher spread0.178 · 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

Quick stats

Citations49
Published2009
Admission routes2
Has abstractyes

Explore more

Same topicSmart Materials for ConstructionFrench-language works237,207