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Record W2753318459 · doi:10.5539/mas.v11n9p131

Introducing a New Idea: Severance of Public Parking in Iran

2017· article· en· W2753318459 on OpenAlexvenueno aff
Masoud Maasoumi

Bibliographic record

VenueModern Applied Science · 2017
Typearticle
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsnot available
Fundersnot available
KeywordsSeveranceUnit (ring theory)BusinessPublic transportPopulationTransport engineeringCivil engineeringEngineeringSociology

Abstract

fetched live from OpenAlex

In 1902, Mozafaredin Shah was familiar with the car on his trip to Europe and brought two cars to Iran. Gradually more cars were brought into the country. Since 1921, the body of Iran's major cities was affected by movement of vehicles. Nowadays, the unbridled use of cars affects Iran's urban management, particularly in cities with a population of more than fifty thousand persons. In addition to the many advantages, the vehicle presence in Iranian cities sometimes has negative consequences. Traffic, noise and air pollution are inevitable disadvantages. Lack of public and private parking is a serious issue for those involved in planning and urban management in Iran, leading to social and economic costs. Lack of parking in Iranian cities is affected by cultural and economic factors and administrative structures. The creation of public parking will not be improved without modification of the factors. Hence, this study introduces a new idea based on the reform approach which resolves a significant part of the problems. This idea is based on the revision and reform of registration rules. A corrective action in the event of operational supports leads to improving the construction of public parking. This new idea provides the severance of public parking and the possibility of issuing the entire document for each unit of parking.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.054
GPT teacher head0.288
Teacher spread0.234 · 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 designBench or experimental
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

Citations1
Published2017
Admission routes1
Has abstractyes

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