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Record W4320916943 · doi:10.18280/ijsdp.180104

Integrative Conservation for Recovering the Riverfront of Mosul Town

2023· article· en· W4320916943 on OpenAlexvenueno aff
Ammar Abdullah Hamad, Emad Hani Ismaeel

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
FundersUniversity of Mosul
KeywordsEnvironmental planningGeographyEnvironmental resource managementArchitectural engineeringEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Mesopotamia has seen the emergence of the dawn of civilizations and the establishment of the first cities on the banks of the Tigris and Euphrates rivers, where many ancient societies have grown from Babylonian, Assyrian and then Islamic to the present time; this requires the conservation of the most prominent historical monuments.The riverfront of the city of Mosul, with its unique and distinguished urban fabric and inhabited until the period before the last war in 2014 AD, was one of the most prominent products of those civilizations.This research attempts to develop a policy to preserve the spirit of the place by reviewing the most critical trends and policies of urban conservation, analyzing many global experiences and explaining international charters.The integrative conservation strategy was adopted by activating community participation.The research applied the method of expert interviews and questionnaires to a sample representing an educated group of society and close to decisionmaking sources, academics and the private sector to obtain qualitative and quantitative data to be statistically analyzed.The research's result was that the policy of conservation and restoration is the closest, followed by the approach of rehabilitation and then urban redevelopment and to the exclusion of the urban renewal policy.

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 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 score0.634
Threshold uncertainty score0.155

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)0.0000.000

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 head0.077
GPT teacher head0.269
Teacher spread0.192 · 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 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

Citations6
Published2023
Admission routes1
Has abstractyes

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