MétaCan
Menu
Back to cohort
Record W2139656263 · doi:10.1061/9780784412473.005

Thermal Effectiveness of the Mitigation Techniques Tested at Beaver Creek Experimental Road Site Based on a Heat Balance Analysis: Yukon, Canada

2012· article· en· W2139656263 on OpenAlexaffabout
J. M-Lepage, Guy Doré, Daniel Fortier

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPermafrostCulvertEnvironmental scienceLeveeSnowBeaverFrost heavingGeotechnical engineeringHydrology (agriculture)GeologyGeomorphology

Abstract

fetched live from OpenAlex

To better understand permafrost degradation under roadways, 12 experimental sections were constructed on the Alaska Highway near Beaver Creek in April 2008. These techniques designed to prevent permafrost thawing are: air convection embankments, heat drains, snow/sun sheds, longitudinal culverts, light-coloured aggregate for road surfacing, snow plowing techniques and grass-covered embankment. This paper presents the results of the analysis on heat balance for each section during their first three years in service to determine the short term effectiveness of the techniques experimented.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.913

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)0.0010.000

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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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 teacher head, 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

Citations16
Published2012
Admission routes2
Has abstractyes

Explore more

Same topicSmart Materials for ConstructionFrench-language works237,207