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Record W146212464

Geothermal Snow-melt System for Bridge Decks (County of Essex, Ontario)

2009· article· en· W146212464 on OpenAlexaboutno aff
T Bateman

Bibliographic record

Venue2009 ANNUAL CONFERENCE AND EXHIBITION OF THE TRANSPORTATION ASSOCIATION OF CANADA - TRANSPORTATION IN A CLIMATE OF CHANGE · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
Fundersnot available
KeywordsBridge deckGeothermal gradientBridge (graph theory)DeckEnvironmental scienceCivil engineeringSnow removalSnowEngineeringRenewable energyGeographyGeologyMeteorology
DOInot available

Abstract

fetched live from OpenAlex

The County of Essex is responsible for the maintenance and construction of 87 bridges. As many freeze-thaw cycles are experienced in our area, Essex County highway bridges are prone to black ice and must be salted on a priority basis for the safety of motorists. However, the long-term effects of this established practice have become obvious. Our wetlands and farmlands are being damaged and our highway bridges require costly deck replacements. A geothermal snow melting or de-icing system is an environmentally-friendly alternative to the common mechanical and/or chemical winter maintenance and is available day and night without a costly stand-by emergency response. A bridge structure which crosses the North Branch of the Cedar Creek within a provincially significant wetland provided an opportunity to be a testing facility to determine the feasibility of utilizing geothermal energy and to assist with the design of other renewable energy systems. The County of Essex used the opportunity provided by the reconstruction of this environmentally-sensitive to pro-actively implement a prototype into the bridge deck. This project was nominated for the TAC 2008 Environmental Achievement Award.

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 score0.606
Threshold uncertainty score0.693

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)0.0000.000

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 head0.016
GPT teacher head0.216
Teacher spread0.199 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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Same venue2009 ANNUAL CONFERENCE AND EXHIBITION OF THE TRANSPORTATION ASSOCIATION OF CANADA - TRANSPORTATION IN A CLIMATE OF CHANGESame topicSmart Materials for ConstructionFrench-language works237,207