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Record W2885757903 · doi:10.5004/dwt.2018.22553

Evaluation of Al-Shamiyah River water quality using the Canadian Council of Ministries of the Environment (CCME) water quality index and factor analysis

2018· article· en· W2885757903 on OpenAlexaboutno aff
Fikrat M. Hassan, Abdul Hameed Al-Obaidy, Ali Obaid Shaawiat

Bibliographic record

VenueDesalination and Water Treatment · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityTurbidityEnvironmental scienceTotal dissolved solidsBiochemical oxygen demandEnvironmental chemistryNitratePollutantAquatic ecosystemEnvironmental engineeringCadmiumChemical oxygen demandChemistryWastewaterEcology

Abstract

fetched live from OpenAlex

ABSTRACT Canadian Council of Ministries of the Environment Water Quality Index (CCME WQI) was used to determine Al-Shamiyah River water quality and its suitability for aquatic life. To calculate CCME WQI, a set of sixteen water quality parameters were evaluated: water temperature (W.T), turbidity (Tur), total dissolved solids (TDS), pH, dissolved oxygen (DO), the biological oxygen demand (BOD5), chlorides (Cl), nitrite (NO 2 ), reactive nitrate (NO 3 ), reactive phosphate (PO 4 ), and dissolved heavy metals (cadmium, copper, chromium, zinc, manganese, lead). In addition, water samples were collected monthly from four sites along Al-Shamiyah River during the period from March 2013 to February 2014. According to CCME WQI analysis, the water quality of Al-Shamiyah ranged from 70.1 to 84.47 at the studied sites, which is considered “Fair–Good”,and was well above the “Marginal” class. The quality of the water is at a desirable level. The water quality seems unaffected by any pollutants that may have entered the river, and it remains at a quality necessary to sustain diverse and sensitive aquatic life. The results of PCA reflected a good look on the water quality monitoring and interpretation of Al-Shamiyah River water.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.153
GPT teacher head0.340
Teacher spread0.187 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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