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Record W2109282634 · doi:10.5539/jsd.v8n8p270

Smart City as Urban Innovation: A Case of Riyadh North-West District

2015· article· en· W2109282634 on OpenAlexvenueno aff
Abdulaziz Nasser Aldusari

Bibliographic record

VenueJournal of Sustainable Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)GeographyCreativityNorth westSmart cityPolitical scienceEngineeringArchaeology

Abstract

fetched live from OpenAlex

Saudi Arabia has recently adopted and implemented an enduring strategy of development that shifts its focal point towards the formulation of knowledge based society. In the same context, KSU (King Saud University), in Riyadh has initiated the project of the Riyadh Techno Valley (RTV), within its campus. The projects aims to strengthen its efforts, in order to develop knowledge based society in Saudi Arabia. KSU as a core of the North-West district of Riyadh had an initiative by adopting a comprehensive idea of Riyadh Knowledge Corridor (RKC) in Prince Turki Alawal Road area. KSU has started to take an active role in setting up new Riyadh’s Smart City node (Smart Riyadh – NWD). The focal point of it is the Riyadh Techno Valley (RTV) project, which is expected to play a central anchored role with other developments in this district such as King Abdul Aziz City for Science and Technology, information technology and communication complex, Saudi Standards, King-Abdulaziz-and-his-Companions-foundation-for-Giftedness-and-Creativity, and king Abdullah financial center. This research study will assesses Riyadh Techno Valley, which will help in reflecting several issues and principals towards the evolution of the North-West district in Riyadh as Smart city.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.036
GPT teacher head0.300
Teacher spread0.264 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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