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Record W4405474297 · doi:10.70102/ijares/v3i1/6

Assessment of the water quality of the mollusa community in the Janabi River-Hayy City of Wasit Province by using Canadian water quality index

2023· article· en· W4405474297 on OpenAlexaboutno aff
Abed I.F., Nashaat M.R., Mirza N.N.A.

Bibliographic record

VenueInternational Journal of Aquatic Research and Environmental Studies · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
FundersUniversity of Baghdad
KeywordsWater qualityGeographyEnvironmental scienceAquatic ecosystemIndex (typography)Hydrology (agriculture)EcologyBiologyGeology

Abstract

fetched live from OpenAlex

The Canadian Environment Council Water Quality Index (CCME-WQ) of the Janabi River water at Hayy City in Wasit Province has been assessed and analysis for over all, drinking water and aquatic life and the impact of the river environment on presence and mollusca community. The samples were collected monthly during 2020-2021, Most of the variables exceeded the Iraqi and global permission limits. It was clear that this index values was marginal category for over all purposes which ranged from 45-48 at all sites, while this index values was poor- marginal categories which ranged from 37-50 for all season. The water quality index values was poor category for drinking purposes which were recorded from 40 -42 for all sites, also it was poor category which was ranging from 31-44 for all season. The values of this index for aquatic life was in the poor-marginal category which ranging from 38-61 for all sites and in the marginal- fair categories which ranging from 61-67 for all season. Nine species of mollusca was identified belonging to seven families. Two species of Melanopsidae and Cyrenidae and one species for Thiaridae, Physidae, Neritidae, Dressseinidae and Unionnoidae. It was concluded that the water of the Janabi River was highly polluted and undrinkable water characterized, as well as, it’s a clearly appeared impact of the river water quality on the mollusca densities

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)0.008
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 score0.097
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.196
GPT teacher head0.441
Teacher spread0.245 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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