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Record W1507875219

Analysis of carpool commuting on slovenian motorways

2011· other· en· W1507875219 on OpenAlexaboutno aff

Bibliographic record

VenueRepozitorij Univerze v Ljubljani (Univerze v Lgubljani) · 2011
Typeother
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsCarpoolTransport engineeringIncentiveOrder (exchange)Public transportRush hourEngineeringBusinessEconomicsFinance
DOInot available

Abstract

fetched live from OpenAlex

The thesis is about carpool. Carpool is an arrangement whereby several participants travel together in one vehicle to the same or nearby destination. Advantages and disadvantages will be presented on some examples from the USA and Canada as well as different systems of carpool. Carpooling is increasing also in Europe and in Slovenia as well. Observations have been made along Slovenian motorways to record sites near motorways access, which are usually not regulated as parking lot, where cars are parked, while commuters continue their journey with other commuters. A survey has been made on some of these sites to achieve data from commuters, who already carpool every day. An additional survey has been distributed to random drivers in order to find people who like carpool as a way to commute every day and potential commuters who would be willing to share their ride with other commuters. Both survey results are presented. In the following section transportation modelling is treated. Special attention will be given to the prioritisation of high-occupancy vehicles. Carpool incentives are provided to encourage carpooling as well as arrangement proposals of sites near motorways access and improvements in order to develop carpool in Slovenia.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.669
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.197
Teacher spread0.185 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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