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Record W4409616912 · doi:10.38035/dit.v1i4.1132

Green Casa Duo Talaga Bestari Tangerang Cluster Design Research

2024· article· en· W4409616912 on OpenAlexaff
Adhi Hermawan, Sigit Wisnuadji, Hilman Rismayadi

Bibliographic record

VenueDinasti Information and Technology · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

This study aims to examine the design and development planning of the Green Casa Duo Cluster in the Talaga Bestari area, Tangerang, which is designed to meet the needs of modern housing that is environmentally friendly and in harmony with nature. With an area of ??270 hectares, this area is equipped with various facilities such as parks, schools, sports clubs, and other recreational facilities that support a healthy and harmonious life for its residents. This study analyzes the concept of housing, planning of facilities and infrastructure, and fulfillment of building technical standards based on regulations in force in Indonesia. The results of the study show that the Green Casa Duo Cluster has succeeded in integrating modern architectural elements with the natural environment, making it an ideal residential area that prioritizes comfort and quality of life.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.065
GPT teacher head0.277
Teacher spread0.212 · 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 designNot applicable
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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