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Record W2100234873 · doi:10.1139/cjce-2013-0458

Methodology of parking analysis

2015· article· en· W2100234873 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsPolytechnique Montréal
FundersVermont Agency of Transportation
KeywordsTransport engineeringTRIPS architectureLand usePublic transportRaw dataParking guidance and informationQuality (philosophy)EstimationRelation (database)BusinessComputer scienceCivil engineeringEngineering

Abstract

fetched live from OpenAlex

Cities are facing many challenges, in particular in relation to the mobility of people and the structure of land use. Parking management, which makes the link between land use and transportation, is one of the crucial ways to meet these challenges. In the Greater Montreal Area, data from origin–destination (OD) surveys is helpful in understanding typical travel behaviour. This study processes car driver trips from travel surveys to develop vehicle accumulation profiles and derive theoretical parking supplies from the observed parking demand, defined as the maximal number of cars parked in an area at a given time. This research also provides an assessment of the quality of the estimation by comparing the parking supplies derived from an OD survey to parking supplies estimated from public geographical information systems and field surveys. The paper shows that parking supply is subject to high variability and highlights that its assessment must take into account regulation data (obtained from on-street regulation parking signs data) that modulates the availability of the raw parking supply according to different days and hours of the day.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.541
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.075
GPT teacher head0.273
Teacher spread0.198 · 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