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Record W7126175378 · doi:10.14710/ijpd.9.1.15-23

Morphology of Ranai City Natuna as the small island border city and sustainable development input

2024· article· W7126175378 on OpenAlexaff
Asa Bintang Kapiarsa, Bagas Dwipantara Putra, Ditasari Nabila, Hendra Priyatna, Delsya Fitri Dewi

Bibliographic record

VenueThe Indonesian Journal of Planning and Development · 2024
Typearticle
Language
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsSustainabilitySustainable developmentSustainable cityService (business)Center (category theory)Urban planningUrban structureUrbanism

Abstract

fetched live from OpenAlex

The Ranai Urban Area is the center and capital of the Natuna Regency, which is spread throughout the East Bunguran District. As the main service center in Natuna Regency, Ranai will directly affect the shape, structure, and environment of the city, as well as the surrounding rural areas. So that the types of forms and structures of the city can be identified during the process. The purpose of this research is to identify the shape and structure of the city of Ranai as an example of a small town in the area of small islands and the borders of Indonesia that has the potential to become a new growth center and has strategic value for the economy, security, and national defense, meanwhile still considering its sustainability for the future, especially in environmental dimension. The factors used to identify the form and structure of cities in this study are ecological and morphological approaches, which used spatial and descriptive qualitative analysis methods. The results of the study show that the shape of the Ranai Urban Area is a city that is not patterned. Spatial structures are sector models from north to east, and some of them have multicore structures from south to west.Furthermore, Ranai is more suitable for adopting the concept of green urbanism for further development, which aligns with the concept of sustainability.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.257
Teacher spread0.226 · 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.

Study designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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