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Record W4249976414 · doi:10.33423/jsis.v15i1.2736

The Problem of Congestion Unreliability Cost: The Certain Error of a Mean and the Measure of Travel Time Utility Gains from Public Works

2020· article· en· W4249976414 on OpenAlexaff
Marc Gaudry

Bibliographic record

VenueJournal of Strategic Innovation and Sustainability · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsTRIPS architectureDuration (music)Measure (data warehouse)Transport engineeringTravel timePublic transportTraffic congestionService (business)Computer scienceStatisticsOperations researchEconometricsEconomicsMathematicsEngineeringBusinessMarketing

Abstract

fetched live from OpenAlex

This summary-for-students presents the claim of some recent analyses of home-based daily urban trips made in France or in the USA that the first four moments of travel time, not just the first, matter and that travelers react to changed service on road or transit networks by adjusting all four of their constructed trip duration moments, including the three higher moments characterizing time unreliability. Sole reliance on mean time changes to evaluate improved or worsened trip conditions then short-changes the benefit-cost analysis and notably fails to explain fast fill-ups and super-peaks that are part of the demanded trip time profile.

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)0.016
metaresearch head score (Gemma)0.106
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.106
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.005
Scholarly communication0.0020.005
Open science0.0030.002
Research integrity0.0010.003
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 head0.067
GPT teacher head0.307
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations1
Published2020
Admission routes1
Has abstractyes

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