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Record W856764546

A Report on the Development of Guidelines for ApplyingRight-Turn Slip Lanes

2015· article· en· W856764546 on OpenAlexaboutno aff
Mason D. Gemar, Zeina Wafa, Jennifer Duthie, Chandra R. Bhat

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
Fundersnot available
KeywordsPedestrianChannelizedSlip (aerodynamics)Transport engineeringEngineeringCivil engineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

This report serves as a summary of the research process regarding the application of right-turn slip lanes in the state of Texas. The work plan was divided into three phases: a review of available literature on the design and operation of right-turn slip lanes, focus group meetings to discuss the synthesis findings with Texas Department of Transportation (TxDOT) representatives, and production of design guidelines pertaining to right-turn slip lanes that accommodate mobility as well as pedestrian and bicyclist safety. The new construction guidance provided for urban and suburban roadways is inspired by the City of Ottawa’s “urban smart channel” design that incorporates a sharp angle of entry into the cross street (~70 degrees) and delineates a narrow turning path for passenger cars using pavement markings. This design promotes slower turn speeds and enhances visibility of the pedestrian crossing location. The sharp angle of entry reduces the head turning required of motorists to search for gaps in oncoming traffic and thus, improves driver comfort. The design includes a crosswalk located in the middle of the channelized roadway that is perpendicular to the turning roadway. The rural design guidance mainly centers on facilitating mobility through the slip lane, as regular pedestrian activity is not typical at rural intersections. Accordingly, the design promotes larger sweeping turns, the use of acceleration lanes, unpaved channelizing islands, and a flatter angle of entry into the cross street. The design guidelines also include a section on retrofitting treatments, targeting issues commonly found at right-turn slip lanes: absence of proper refuge for pedestrians, motorist noncompliance in yielding to crossing pedestrians, pedestrian noncompliance with the crosswalk location, high speeds in the channelized roadway, low visibility of crossing pedestrians, and excessive head turning to spot oncoming traffic.

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)0.063
metaresearch head score (Gemma)0.086
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.063
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.086
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0090.004
Science and technology studies0.0050.003
Scholarly communication0.0080.006
Open science0.0070.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0210.012

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 head0.123
GPT teacher head0.303
Teacher spread0.180 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2015
Admission routes1
Has abstractyes

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