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Record W2022065938 · doi:10.3141/2155-18

Experimental Short-Wavelength Surface Textures in Portland Cement Concrete Pavements

2010· article· en· W2022065938 on OpenAlexaffabout
Christopher R. Byrum, C Raymond, M Swanlund, T Kazmierowski

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2010
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsPortland cementWavelengthSkid (aerodynamics)Materials scienceTexture (cosmology)Surface finishGeotechnical engineeringTransverse planeChristian ministryCementForensic engineeringEngineeringGeologyComposite materialStructural engineeringComputer scienceLaw

Abstract

fetched live from OpenAlex

A cooperative research effort was undertaken by FHWA and Canada's Ministry of Transportation for Ontario (MTO) regarding experimental texturing of fresh portland cement concrete pavement. The goal of the research was to develop techniques that can fabricate surface textures having most of the aggressive texture size wavelength content within the 2- to 8-mm (80- to 300-mil) wavelength range, with mean texture depth size at approximately 1 mm (40 mil). This wavelength range is relatively short, and it is difficult to fabricate ultraflat textures with elevation variation only in this wavelength range. The research was initiated by FHWA, and an experimental texture test site was constructed in Ontario, Canada, under the guidance of the MTO. Five texture test sections were constructed and evaluated at the Ontario test site. The short wavelength transverse textures averaging approximately 8-mm (315-mil) spacing are quieter and appear to offer equal or better skid resistance than conventional deeper transverse tining having 16-mm (630-mil) groove spacing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.063
GPT teacher head0.359
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicInnovative concrete reinforcement materialsFrench-language works237,207