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Record W1830612426 · doi:10.1139/cjce-2014-0423

Field evaluation of the performance of alternative deicers for winter maintenance of transportation facilities

2015· article· en· W1830612426 on OpenAlexafffundvenue
Kamal Hossain, Liping Fu, Roberto Lake

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsSnowSnow removalEnvironmental scienceHighway maintenanceTransport engineeringCivil engineeringEngineeringMeteorology

Abstract

fetched live from OpenAlex

This paper presents the results of an extensive field study on the comparative performance of alternative materials for snow and ice control of transportation facilities. Approximately 300 tests were conducted in a real-world environment, covering four alternative materials, and 21 snow events. Each of the alternatives tested were compared to regular rock salt in terms of snow melting performance — bare-pavement regain time. The study confirmed the relative advantage of these alternatives over the regular salt, but also showed that their performance varied largely depending on some external conditions. Performance models were calibrated and then used for developing application rate adjustment factors that can be applied by maintenance operations for determining the optimal application rates for specific weather events and pavement conditions. The applicability of the results is limited to parking lots and sidewalks without the traffic effects, and as such cannot be easily applied to winter roadways maintenance.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.972

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 head0.015
GPT teacher head0.201
Teacher spread0.185 · 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 designSimulation or modeling
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

Citations20
Published2015
Admission routes3
Has abstractyes

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