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Record W4406699887 · doi:10.21608/erjsh.2020.405713

Evaluation of Water Quality Index for Bahr Shebin Canal in Egypt

2020· article· en· W4406699887 on OpenAlexaboutno aff
Neveen B. Abdelmageed, W. A. Fahmy, H. A. Elgzzar

Bibliographic record

VenueEngineering Research Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsIndex (typography)Water qualityQuality (philosophy)Environmental scienceComputer sciencePhysicsBiology

Abstract

fetched live from OpenAlex

Canadian Council of Ministers of the Environment Water Quality Index CCME-WQI is considered one of the most used global indices to evaluate water surfaces. Bahr Shebin Canal is an important canal in middle delta as it serves three big governorates Menofya, Gharbia and Kafr EL-sheikh. Therefore, the aim of this paper is to evaluate the water quality of Bahr Shebin Canal for irrigation use. The evaluation of the canal based on data collected monthly by drainage Research Institute DRI through National Water Quality Monitoring Network NWQMN project from August 2017 to July 2018. The index outputs are numbers between zero to 100 that reflect the water quality status of the canal. Evaluation results for the monitoring points along Bahr shebin canal were fair.

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)0.013
metaresearch head score (Gemma)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
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)0.0020.000

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 head0.258
GPT teacher head0.445
Teacher spread0.187 · 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 designSimulation or modeling
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
Published2020
Admission routes1
Has abstractyes

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