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Record W4372346367 · doi:10.18280/ijsdp.180413

Proposed Sustainable Indicators to Assess Transport Sustainability in Baghdad City

2023· article· en· W4372346367 on OpenAlexvenueno aff
Areej Muhy Abdulwahab, Nabil T. Ismael, Wameedh T. M. Altameemi, Hanan Musa

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
FundersMustansiriyah University
KeywordsSustainabilityEnvironmental planningSustainable transportBusinessSustainable developmentUrban sustainabilitySustainable cityEnvironmental resource managementEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

The aim of the present work is to choose the most important sustainable urban indicator according to the opinion of local transport specialists, and using it to evaluate the urban transportation system in Baghdad city.To achieve these objectives, make Questionnaire form content 130 indicators were obtained in various environmental, social and economic dimensions.The questionnaires were analyzed using SPSS program; and Likert Scale (fivepoint) is adopted (5 very effective, 1 not very effective) to find out the importance and impact of each indicator at the local level.The results of the questionnaire showed that the most important sustainable indicator that can be applied and that has a very strong impact on the local Iraqi reality, is the accessibility indicator to public services and public transport, its relative importance was 93.6%, and 91.2% for the mobility management indicator.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.288
Teacher spread0.266 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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