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Record W2506816565 · doi:10.5539/mas.v10n11p90

Studying Quality Factors of Townscape in Coasts Case Study: Joffre Neighborhood Center in Persian Gulf Coast of Boushehr

2016· article· en· W2506816565 on OpenAlexvenueno aff
Rahil Nadoomi, Zahra Shamsi, Maryam Nikbakht Dehkordi

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture and Cultural Influences
Canadian institutionsnot available
Fundersnot available
KeywordsPersianIndustrialisationNatural (archaeology)Quality (philosophy)GeographyBalance of natureEnvironmental planningEcologyArchaeologyLawPolitical science

Abstract

fetched live from OpenAlex

Men’s tendency and requirement have been increased for being represented in natural areas in the city through industrialization and cities development. On the one hand, the necessity of surviving of urban damaged and dense areas and protecting and improvement of natural resources in cities and on the other hand, the townscape has been considered because of increasing the quality of urban spaces of environment in nature. Based on these views, surviving sea coasts, wharfs, green spaces, making connection among them and urban residential areas require coordination between environmental approaches and urban issues and solutions should be chosen to provide a balance among urban, aesthetic and ecology approaches. The present essay attempts to study the concept of townscape quality through descriptive-analysis method by considering Joffre coastal neighborhood center in western south of Boushehr as a part of coastal townscape and effective indicators on its quality and present solutions for promoting and improving the quality of coastal townscape in the studied part.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.069
GPT teacher head0.292
Teacher spread0.223 · 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 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
Published2016
Admission routes1
Has abstractyes

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