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Record W2334908128 · doi:10.1061/40976(316)552

An Environmental Security and Water Resources Management System Using Real Time Water Quality Warning and Communication for the Nile River

2008· article· en· W2334908128 on OpenAlexaff
Amir Ali Khan, Haseen Khan

Bibliographic record

VenueWorld Environmental and Water Resources Congress 2008 · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsDepartment of Environment and ConservationGovernment of Newfoundland and Labrador
Fundersnot available
KeywordsWater resourcesWarning systemWater securityWater qualityEnvironmental resource managementEarly warning systemEnvironmental securityComputer scienceQuality (philosophy)Environmental scienceComputer securityEnvironmental planningTelecommunications

Abstract

fetched live from OpenAlex

Through a NATO "Science for Peace" Project initiated in July 2007 an environmental security and water resources management system using real time water quality warning and communication is being researched and developed for the Nile River in Egypt. Real time water quality warning will be provided through a four station Real Time Water Quality monitoring index network. In parallel, an Egyptian Water Quality Index will be developed. This paper describes the project and describes the progress accomplished in the first year of the project. It describes the current water quality sampling network in Egypt and highlights how the NATO "Science for Peace" Project will build upon and augment the existing network. It highlights the challenges encountered in establishing the environmental security and water resources management system. The paper also describes how a key objective of the project is to train young scientists in Egypt. This research will be relevant to NATO concerns under the two categories of Environmental Security and Water Resources Management. The project will allow Egypt to ensure environmental security of its water bodies and enhance integrated water resources management.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.999

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 studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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