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Record W4392199748 · doi:10.18280/mmep.110202

The Environmental Impact of Pollutants and Heavy Materials on the Water Quality in the Tigris River

2024· article· en· W4392199748 on OpenAlexvenueno aff
Mahmood S. Al-Saedi, Sepanta Naimi, Zainab T. Al‐Sharify

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
FundersMinistry of EnvironmentMustansiriyah UniversityUniversity of Birmingham
KeywordsPollutantEnvironmental scienceWater qualityHeavy metalsEnvironmental engineeringWater resource managementEnvironmental chemistryEcologyChemistry

Abstract

fetched live from OpenAlex

This research aims to understand the characteristics of the Tigris River and the possibilities of human use in Baghdad.Samples for this study were collected for analysis from three separate districts in Baghdad, Iraq.Three sites in the upstream, middle, and lower downstream regions of the study area were used to collect river water samples (East Tigris Water Project, Al-Shuhada Bridge Project, and Al-Rasheed Project).To verify that the water is suitable for human needs including drinking water, agriculture, and industry, several tests have been carried out; The study data from the year (2005-2020) PH, Cl, NO3, PO4, SO4, Na, Ec, Ca, K, Mg, TH and TDS are among these tests.And the results of the three projects in the water characteristics of the Baghdad River.The results showed that SO4 was within the allowed in (East Tigris Water Project, and Al-Shuhada Bridge Project) and was higher than allowed in Al-Rasheed Project, while (PH, NO3, PO4, Ca, TH, and K) were all within the allowed range (Project East Tigris Water, Al-Shuhada Bridge Project).According to the World Health Organization, Ec had readings a few above the permissible levels and the TDS was above the permissible limit.

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 categoriesnone
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 score0.058
Threshold uncertainty score0.153

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 studies0.0000.000
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 head0.033
GPT teacher head0.259
Teacher spread0.226 · 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 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
Published2024
Admission routes1
Has abstractyes

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