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Record W969218633 · doi:10.14796/jwmm.r245-20

Sustainable Development and the Red Sea-Dead Sea Canal Project

2012· article· en· W969218633 on OpenAlexaffvenue
Marc A. Rosen, Yousef Nazzal

Bibliographic record

VenueJournal of Water Management Modeling · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsDead seaOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

Sustainability is critically important for human development.The concept of sustainable development embodies the view that social, economic and environmental objectives should be complementary and interdependent.Sustainable development requires policy changes across sectors and coherence among them, and entails balancing society's economic, social and environmental objectives, integrating them through mutually supportive policies and practices, and making appropriate tradeoffs.The Red Sea-Dead Sea Canal project (RSDSC) is an example of a megaproject that may contribute significantly to sustainable development.This chapter examines the manner in which the RSDSC contributes to the key factors for sustainability, along with the positive and negative environmental and socio-economic impacts of the project.The large amount of desalinated water expected from this project will be of great significance to partners in the region.The stratification and dilution of the Dead Sea water mass with sea water may cause losses for companies, the precipitation of gypsum, and changes in the environment of the upper water mass.The feasibility of this project must be thoroughly studied.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.035
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.030
GPT teacher head0.268
Teacher spread0.238 · 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
Published2012
Admission routes2
Has abstractyes

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