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Record W2241809640

EFFECT OF DARKNESS ON THE CAPACITY OF LONG-TERM FREEWAY RECONSTRUCTION ZONES

2000· article· en· W2241809640 on OpenAlexaboutno aff
Ahmed Al‐Kaisy, F L Hall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsDarknessDaylightWork (physics)Transport engineeringTerm (time)Environmental scienceGeographyEngineeringBiologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents an investigation into the effect of darkness on freeway capacity at long-term reconstruction sites. It is part of ongoing research to examine the factors that affect freeway capacity at work zones. Capacity data from two work sites in Ontario, Canada were examined. At each site, capacity observations during the PM peak period were recorded on weekdays before and after the change from Eastern Daylight Time to Eastern Standard Time. Data from video records were then processed using 5-min intervals. Heavy vehicles were converted to passenger car equivalents using the HCM equivalency factors. Study results suggest that darkness has a significant effect on freeway capacity at freeway reconstruction work zones. However, darkness affected capacity differently at the two sites investigated. At one site, the decline in freeway capacity due to darkness was found to be 7.5 % while this decline was found to be only 3.25 % at the other site. The study linked this difference to the effect of grade at the second site. This, in turn, suggests that the compound effect of two or more variables on freeway capacity at reconstruction sites is interactive rather than additive, which is consistent with findings from previous stages of this research. 1.

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 categoriesInsufficient payload (model declined to judge)
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 score0.999

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)0.0010.000

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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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

Citations15
Published2000
Admission routes1
Has abstractyes

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