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Record W4306148590 · doi:10.5267/j.ccl.2022.8.009

Studies on Nile river pollution and water quality indicators in Egypt

2022· article· en· W4306148590 on OpenAlexvenueno aff
Ahmed M. K. Abouhalima, Yingxia Li

Bibliographic record

VenueCurrent Chemistry Letters · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityPollutionHydrology (agriculture)Nile deltaAgricultureEnvironmental scienceWater pollutionWater resource managementChemistryGeographyEnvironmental chemistryEcologyGeologyBiologyArchaeology

Abstract

fetched live from OpenAlex

The Nile River is an important natural and exclusive source of fresh water in Egypt. Water samples were taken monthly from twelve sites from 2015 to 2020 in El Beheira Governorate and eighteen physicochemical parameters were measured. The results show that the Rahawy drain recorded the highest values for most of the physicochemical parameters. The HPI and MI indicators in Rahawy drain were higher (70 % & 100 %) than in other sites, especially in the summer and winter seasons. The Rahawy WQI values were classified as poor quality. The IWQI results indicate that the water quality for the Rahawy was within the "severe restriction" class, with many restrictions to be used in agriculture. The water quality of the Nile River in the south of Egypt is better than that of the north and the water quality recovery takes more time and distance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
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 head0.040
GPT teacher head0.318
Teacher spread0.278 · 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 designBench or experimental
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

Citations2
Published2022
Admission routes1
Has abstractyes

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