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Record W7084299986

Evaluation of Groundwater Quality Using WQI Models and Its Application to Plants Vulnerable to Ecological Stress

2025· article· en· W7084299986 on OpenAlexaboutno aff

Bibliographic record

VenueCyberLeninK (CyberLeninka) · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsGroundwaterWater qualityHydrology (agriculture)NitrateLimitingTotal dissolved solids
DOInot available

Abstract

fetched live from OpenAlex

This study focuses on the groundwater found at depths of 10-20 meters in the Amudarya district of the Republic of Karakalpakstan, within Uzbekistan. The primary objective of the research is to determine the suitability of this water for irrigating plants that are not resistant to environmental stress. Water samples were collected from 12 wells over the period of 2020-2024, and laboratory analyses were conducted based on four key indicators: Total Dissolved Solids (TDS), chloride (Cl⁻), potential of Hydrogen (pH), and nitrate (NO₃⁻). To assess the overall water quality, the “Weighted Arithmetic Water Quality Index (WA-WQI)” and the “Canadian Council of Ministers of the Environment (CCME)” models were used. According to the research findings, the overall quality of groundwater in the Amudarya district falls under the “Unsuitable for drinking and fish culture” category according to the WA-WQI model and the “poor” category according to the CCME WQI model, limiting its use for irrigating plants with low tolerance. The novelty of this study lies in the confirmation that groundwater is unsuitable for irrigating plants that are not resistant to environmental stress. However, it can be used for irrigating certain semi-tolerant and tolerant plant species.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.070
GPT teacher head0.342
Teacher spread0.272 · 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.

Study designBench or experimental
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

Explore more

Same venueCyberLeninK (CyberLeninka)Same topicNeutrophil, Myeloperoxidase and Oxidative MechanismsFrench-language works237,207