MétaCan
Menu
Back to cohort
Record W561416141

Static Progress: In Canada, the Calgary Parking Authority has been Piloting the Use of Vehicle-Mounted Laser Detectors to Increase the Productivity and Personal Safety of those Involved in Parking Enforcement

2006· article· en· W561416141 on OpenAlexaboutno aff
Mike Clarke

Bibliographic record

VenueITS International · 2006
Typearticle
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementLicenseTransport engineeringLaptopGlobal Positioning SystemLaw enforcementProductivityEngineeringComputer securityComputer scienceAutomotive engineeringAeronauticsTelecommunicationsLaw
DOInot available

Abstract

fetched live from OpenAlex

In an article about the use of Intelligent Transportation Systems (ITS) in enforcement of parking and other regulations, the Calgary Parking Authority’s use of vehicle-mounted laser detectors is described. In a pioneering study in the summer of 2006, the city replaced its old chalking system with ITS techniques. Alternatives are needed because chalking is labor-intensive and can expose employees to bad weather and angry motorists. The study used an automatic chalking system that employs a laser scanner, color cameras (for license plate and vehicle profile photos) and GPS, all linked to a laptop in the enforcement vehicle. The enforcement vehicle is mounted with a number of scanners enabling it to register a profile unique to each parked vehicle, log it into the database and compare it to earlier records to determine if a vehicle has exceeded its permitted time. Tickets were automatically generated and issued to the person associated with the license plate number. Additional trials are expected.

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)0.001
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 score0.290
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.041
GPT teacher head0.268
Teacher spread0.227 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueITS InternationalSame topicSmart Parking Systems ResearchFrench-language works237,207