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Record W2088208555 · doi:10.3141/2060-05

Length Requirements for New Single-Arc Unsymmetrical Vertical Curve

2008· article· en· W2088208555 on OpenAlexafffund
Said M. Easa

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2008
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsToronto Metropolitan University
FundersCore Research for Evolutional Science and TechnologyNatural Sciences and Engineering Research Council of Canada
KeywordsArc lengthArc (geometry)CurvatureOsculating circleMathematicsGeometryFunction (biology)Curve fittingPoint (geometry)Mathematical analysisStatistics

Abstract

fetched live from OpenAlex

Traditional unsymmetrical vertical curves consist of two parabolic arcs smoothly connected at the point of common curvature. A new single-arc unsymmetrical vertical curve that takes the form of a cubic instead of parabolic function has been recently developed. The curve has a rate of change in grade that gradually varies between the start and end of the vertical curve. The single-arc curve eliminates the sudden change that exists in curvature of traditional two-arc unsymmetrical vertical curves. This paper first develops the sight distance (SD) relationships for the new single-arc curve (crest type). With these relationships, the SD profile for the new curve is established and its shape shows a substantial improvement over the abrupt-type SD profiles of the two-arc curves. The length requirements that satisfy stopping, passing, and decision SD guidelines of AASHTO are then presented. Some examples are used to illustrate the use of the developed design aids. The new single-arc curve builds on previously developed unsymmetrical vertical curves to improve curve characteristics that hopefully will promote road safety.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.187
GPT teacher head0.383
Teacher spread0.196 · 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.

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

Citations2
Published2008
Admission routes2
Has abstractyes

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