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Record W2996583662 · doi:10.2478/ohs-2019-0031

Integrated approach to quality indices and health risk assessment of water in the Bahr Yusuf Canal, Fayoum, Egypt

2019· article· en· W2996583662 on OpenAlexaboutno aff
Mohamed E. M. Hassouna, Mohamed E. Goher, Seliem M. El-Sayed, Reda A.A.A. Hassan

Bibliographic record

VenueOceanological and Hydrobiological Studies · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityEnvironmental scienceHazard quotientHazardPollutionAquatic ecosystemWater resource managementToxicologyEnvironmental healthEnvironmental engineeringHuman healthEnvironmental chemistryEcologyMedicineBiologyChemistry

Abstract

fetched live from OpenAlex

Abstract The Bahr Yusuf Canal is the life artery of the Fayoum Province, which provides the province with two thirds of the freshwater quota from the Nile River. The present work was carried out to assess the suitability of water in the Bahr Yusuf Canal for various purposes and to assess the potential health risk associated with metal content. The results showed that the water quality of Bahr Yusuf was classified as poor and very poor for recreational use according to the Oregon WQI. On the other hand, the Aquatic Toxicity Index indicated the suitability of water for all fish species. The Canadian WQI and the Weighted Arithmetic WQI classified the canal water as good (WQI = 92), fair (WQI = 73) & marginal (WQI = 64) and excellent, poor to good & good to excellent for irrigation, drinking and aquatic life, respectively. Despite the significant contamination of water with heavy metals (as indicated by the Heavy Pollution Index, ranging from 104.44 to 206.32, from 16.81 to 38.48 and from 219.07 to 472.24 μg l −1 ), the Hazard Quotient (HQ) and the Hazard Index (HI) data indicate that water of Bahr Yusuf does not pose a human health risk through ingestion or dermal contact. In general, the study showed that water in the Bahr Yusuf Canal is characterized by different levels of pollution, which requires rapid and critical intervention by responsible authorities to prevent the discharge of different types of waste and further deterioration of the water quality during the lifetime of the channel and its subsequent rehabilitation.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.105
GPT teacher head0.364
Teacher spread0.259 · 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 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

Citations11
Published2019
Admission routes1
Has abstractyes

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