MétaCan
Menu
Back to cohort
Record W4292880498 · doi:10.53730/ijhs.v6ns6.11892

ISO urban quality to measure the level of efficiency of urban transport

2022· article· en· W4292880498 on OpenAlexaboutno aff
Abdulkareem Adil Al-Ani, Moheeb Kamel Al-Rawai

Bibliographic record

VenueInternational Journal of Health Sciences · 2022
Typearticle
Languageen
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStandardizationBusinessCertificateRegional scienceQuality (philosophy)Transport engineeringMeasure (data warehouse)Environmental planningGeographyEnvironmental economicsComputer scienceEngineeringEconomics

Abstract

fetched live from OpenAlex

Providing and improving city services is critical to local governments, decision-makers, planners, and international and civil society organizations. Therefore, the International Organization for Standardization (ISO) sought to develop the standard specification 37120 under the name (Sustainable Cities and Communities - Indicators of city services and quality of life) to measure the efficiency of services for cities and to grant it the ISO certificate in urban quality through a set of indicators for various areas of life in the city. Including the field of urban transport is the basis of development and is directly related to the lives and jobs of the city's residents, where the efficiency of urban transport in the study area (the city of Fallujah) will be known in light of the ISO 37120:2018 standard and compared with the cities (Amman and Toronto) using statistical analysis programs, where the results showed fairly equal between the two cities (Fallujah and Amman) and a large gap between the two cities (Fallujah and Toronto). The research suggested making improvements to the transportation network in the study area.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.098
GPT teacher head0.335
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Health SciencesSame topicUrban Transport Systems AnalysisFrench-language works237,207