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Record W4388907483 · doi:10.36040/pawon.v7i2.5294

KAJIAN METODE ARSITEKTUR BIOKLIMATIK PADA RUMAH ADAT BANJAR GAJAH BALIKU

2023· article· en· W4388907483 on OpenAlexaff
Farah Hafizha, Sarifah Nur Isra Jairina

Bibliographic record

VenuePawon Jurnal Arsitektur · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsArchitectureVernacular architectureVernacularDocumentationArchitectural engineeringResearch ObjectArchitectural designCivil engineeringHistoryArchaeologyGeographyComputer scienceEngineeringArtRegional science

Abstract

fetched live from OpenAlex

Bioclimatic architecture is a design approach that considers the relationship between architectural forms and the local climate. Vernacular architecture is an architectural design that adapts to the local climate, local construction materials and techniques, influenced by social, cultural and economic aspects of the local community. The ancient architecture of the Gajah Baliku traditional house in South Kalimantan has been around since the 1800s and is part of the vernacular architecture. This study discusses the bioclimatic architectural methods found in the traditional house of Banjar Gajah Baliku. The method used in this study is a qualitative descriptive method which aims to find out how the application of bioclimatic architectural methods to the traditional house of Banjar Gajah Baliku. The data collection method was obtained from primary sources, namely literature which was carried out to find the theoretical basis and become a reference in reviewing empirical data, as well as field observations consisting of measurements, sketches, documentation and redrawing the research object. From this study, it is concluded that the traditional house of Banjar Gajah Baliku in South Kalimantan has met the nine criteria of the bioclimatic architectural method.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.044
GPT teacher head0.227
Teacher spread0.183 · 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 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
Published2023
Admission routes1
Has abstractyes

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