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Record W3172835590 · doi:10.1051/e3sconf/202126305043

Dealing with heritage Hanoi Old Quarter

2021· article· en· W3172835590 on OpenAlexaboutno aff
Dung Ngo Thi Kim

Bibliographic record

VenueE3S Web of Conferences · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Crisis of the 21st Century
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanizationQuarter (Canadian coin)ArchitectureArchitectural engineeringPopulationUrban planningBusinessComputer scienceRegional scienceGeographyCivil engineeringEconomic growthSociologyEngineeringEconomicsArchaeologyDemography

Abstract

fetched live from OpenAlex

Properly solving the relationship between conservation and devel-opment is one of the important requirements in the development of historic urban. The author approaches the issue through case studies of the old Quarter, a special historical sites of Hanoi capi-tal. The process of urbanization and urban development has af-fected and made Hanoi Old Quarter (HOQ) many changes. How to maintain HOQ has been studied by many scientists. Some of the results of those studies have been applied in practice. Howev-er, the results are still moderate. This study focuses on compre-hensive review of the features of HOQ and its transformation in both tangible and intangible aspects. The author used the field survey method and secondary data for research. The results of the study have shown the characteristics of HOQ along with its changes in the aspects of economy, culture, society, science-technology and architecture-planning. The current status of HOQ is: Population density is too high; altered traditional functions; space, architecture and landscape are deformed and its characteristic elements are gradually lost; polluted environment, technical infrastructure are overloaded. The article al-so discusses the direction to maintain and develop HOQ as a his-torical sites without hindering the development of smart and sus-tainable urban development..

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.206
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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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