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Record W4233051198 · doi:10.21271/zjpas.33.s1.1

Assessment of Groundwater Quality over the Erbil Plain Based on Water Quality Index

2021· article· en· W4233051198 on OpenAlexaboutno aff
Bakhtyar Abdullah Othman, Esmail S. Ibrahim

Bibliographic record

VenueZANCO Journal of Pure and Applied Sciences · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsGroundwaterIndex (typography)Quality (philosophy)Environmental scienceWater qualityWater resource managementHydrology (agriculture)GeologyComputer scienceGeotechnical engineeringBiologyEcologyPhysics

Abstract

fetched live from OpenAlex

Groundwater is used for drinking, household and agricultural activities by the growers surrounding Erbil city. Therefore, it was necessary to determine its quality by measuring physical and chemical parameters according to standard method. Thus, water samples have been collected from sixteen wells during December 2016, March, Jun, and September 2017 within 1liter polyethylene bottles and transported to the laboratory for analysis and analyzed according to Canadian Water quality Index Formula (WQI). The WQI of groundwater was based on 22 parameters including pH, electrical conductivity, total hardness, calcium hardness, magnesium hardness, total alkalinity, chloride, dissolved oxygen, biological oxygen demand, sodium, potassium, sulphate, orthophosphate, nitrate, oil and grease, zinc, copper, iron, nickel, lead, cadmium and mercury. WQI was found to be 38.87, which indicates a poor quality that the water was not suitable for direct consumption and must be treated before use to avoid water-related diseases.

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)0.000
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 score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.037
GPT teacher head0.331
Teacher spread0.294 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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