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Record W2463285300 · doi:10.19026/rjaset.10.1832

Evaluation of Treated Water at Three Adjacent Water Treatment Stations in Al-Hilla City, Iraq by Using CCME Water Quality Index

2015· article· en· W2463285300 on OpenAlexaboutno aff
Layla Abdulkareem Mokif

Bibliographic record

VenueResearch Journal of Applied Sciences Engineering and Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsIndex (typography)Environmental scienceWater qualityComputer scienceBiology

Abstract

fetched live from OpenAlex

In this study, many water quality indices are reviewed. The Canadian Council of Ministers of the Environment (CCME), Water Quality Index (WQI) is used in the assessment of three adjacent water treatment stations. These stations are in Al-Hilla City in Iraq. They are all supplied with raw water from Shatt Al-Hill River. For determining the water quality of these water treatment stations, eight physical and chemical parameters are estimated. The considered parameters are Alkalinity (Alk), Turbidity (Turb.), Chloride (Cl), pH, Magnesium (Mg), Electrical Conductivity (EC), Calcium (Ca) and Total Hardness (TH). Treated water samples were collected and tested regularly for 6 months from the three stations. The calculated results for water quality reveal that all selected water treatment stations are good according to classification of CCME WQI. All the estimated values of the chemical and physical parameters concerning the studied water treatment stations are ranging within the Iraqi standards except turbidity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.194
GPT teacher head0.406
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2015
Admission routes1
Has abstractyes

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