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Record W1982019640 · doi:10.2495/ut150141

Solving parking issues: a case study of Abu Dhabi city

2015· article· en· W1982019640 on OpenAlex
Mahmoud I. Dibas, A. Al Jassmi, Mostafa M. Ibrahim

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.

Bibliographic record

VenueWIT transactions on the built environment · 2015
Typearticle
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsTransport Canada
Fundersnot available
KeywordsAbu dhabiTransport engineeringEnforcementScope (computer science)Environmental planningBusinessLegislationPlan (archaeology)Civil engineeringEngineeringComputer scienceGeographyPolitical science

Abstract

fetched live from OpenAlex

Abu Dhabi has grown tremendously over a brief period of time. With this rapid growth there are usually growing pains. Knowing that the city would be of significant size and densely populated the road system was constructed with high capacities. Although these considerations were made for the movement of vehicles, it seems that the storage of these same vehicles was not given the same level of consideration. The road system was designed, but early on parking requirements was not enforced.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.599

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 head0.073
GPT teacher head0.276
Teacher spread0.203 · 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