MétaCan
Menu
Back to cohort
Record W2154628046 · doi:10.3141/2272-15

Field Test of Organic Deicers as Prewetting and Anti-Icing Agents for Winter Road Maintenance

2012· article· en· W2154628046 on OpenAlexaff
Liping Fu, Raqib Omer, Chaozhe Jiang

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSnowIcingEnvironmental scienceBrineSalt (chemistry)Environmental engineeringMeteorologyChemistryGeography

Abstract

fetched live from OpenAlex

Salts, in both solid and liquid forms, are used in winter road maintenance because of their effectiveness in breaking and preventing the bonding of snow and ice to road surfaces. Because of the detrimental effects of salt on infrastructure and the environment, many alternative materials are being tested for snow and ice control during winter. This paper summarizes the results of field tests that compared two beet molasses–based materials with regular salt and salt brine when used as prewetting and anti-icing agents. The performance comparison was based on more than 100 h of friction readings along with high-resolution image data collected over nine snow events. Application rates, test route, and comparison methodology along with experimental results, recommendations, and potential for future research are also presented.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.046
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.343
Teacher spread0.298 · 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

Citations40
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicSmart Materials for ConstructionFrench-language works237,207