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Record W2092313169 · doi:10.1061/40730(144)14

Stated Response Examination of Factors Influencing Commercial Movement Route Choice Behavior

2004· article· en· W2092313169 on OpenAlexaffabout
John Douglas Hunt, John E. Abraham

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCredenceTollSensitivity (control systems)Work (physics)Toll roadData collectionValue of timeSelection (genetic algorithm)Value (mathematics)Computer scienceTransport engineeringOperations researchStatisticsEconometricsTravel timeMathematicsEngineeringMedicine

Abstract

fetched live from OpenAlex

A stated response experiment was performed to examine how people in Montreal in Canada are influenced by specific route attributes in the selection of routes for commercial movements. The route attributes considered included the expected driving time, the roadway type (arterial or freeway), the magnitude of a toll and the toll collection method (if any), and the probability and associated magnitude of a possible delay. A total of 242 complete interviews were conducted in two separate surveys, one with commercial drivers and the other with trucking company operators. With multiple observations of choice behaviour obtained in each interview, a total of 1885 observations of the relevant route choice behaviour were obtained. Analysis of these observations indicates that all the included attributes other than toll collection type have significant effects on route choice in the situation being considered. They also indicate, among other things, that the probability of delay has a very large impact, that the sensitivity to time in delay is greater than the sensitivity to expected driving time, and that the implied value of driving time is impacted dramatically by the nature of the treatment of expected delay. Some of these results are consistent with findings in related work done by others, which is seen to add credence to the approach being used here. Some of these results are novel, with implications for other future work.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.995

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)0.0000.000

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 head0.032
GPT teacher head0.317
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations17
Published2004
Admission routes2
Has abstractyes

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