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Record W4413858918 · doi:10.31272/jeasd.2903

Assessment of the Water Quality of the Tigris River in the City of Mosul

2025· article· en· W4413858918 on OpenAlexaboutno aff
Faiza I. Muhammed, İlker Akmırza

Bibliographic record

VenueJournal of Engineering and Sustainable Development · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)GeographyWater resource managementEnvironmental scienceWater qualityHydrology (agriculture)GeologyGeotechnical engineeringEcologyBiologyPhilosophy

Abstract

fetched live from OpenAlex

In this study, a total of 120 water samples were collected from five stations along the Tigris River within Mosul City and tested to assess their quality. Water samples were collected over the course of a year. The study included determining thirteen physical, chemical, and biological parameters of the water. The water quality assessment for river water was done using the Weighted Arithmetic Water Quality Index Method (WA WQI), the Canadian Council of Ministry of Environment (CCME WQI), and the method developed by Erdenebayar. The test results showed that the parameters included in the study were within the allowable limits. The overall results of the water quality index revealed that the water quality can be classified as good, which means that the water still meets the different domestic, industrial, aquatic life, and agricultural needs. The maximum water quality index values were 36, 81, and 79, and the minimum values were 18, 76, and 35 for the WA WQI, CCME WQI, and E WQI methods, respectively. A slight difference in water quality was detected during the different seasons, with a slight deterioration in its quality as water flows from north to south. Generally, a good agreement was observed among the three methods.

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)0.003
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 score0.120
Threshold uncertainty score0.121

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0000.000

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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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