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Record W4323250764 · doi:10.58629/ijaq.v11i1.200

Assessment of Water Quality of Shatt al Arab River in north of Basra

2022· article· en· W4323250764 on OpenAlexaboutno aff
Roaa H. Abbass, Jabbar Kh Abdul-Hussan, Amjed K. Resen

Bibliographic record

VenueIRAQI JOURNAL OF AQUACULTURE · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityEnvironmental scienceNitrateHydrology (agriculture)SalinityPhosphateNitriteRange (aeronautics)Environmental chemistryAnimal scienceChemistryEcologyGeologyBiology

Abstract

fetched live from OpenAlex

The present study was aimed to ecological evolution for the north part of Shatt Al Arab River, by using water quality index (WQI, Canadian Model) because the efficiency of this method to volutes fresh water quality and to determinate the water quality for different uses. This study has been done through the period between December, 2012 to November, 2013; samples were collected monthly during low tide, three stations have been chosen, the first one was near Al Hartha area, the second station was near Al Hartha area and the third station was near Saeed Ali Al Noor Bridge. The present results were showed that water temperature were ranged between 13.8 ºC – 37 ºC and dissolved solids were 100—1670 mg/l, , salinity range were 0.6-2.5 ‰, the range of dissolved oxygen was 5.7-10.7 mg/l, the hardness value was range between 500-1120 mg magnesium ions was 35-93 mg/l, nitrite was 3.5-15 μg nitrogen atom-nitrate/l, the range of phosphate was 0.05-0.5 μg phosphor atom-phosphate /l, phosphorous range was 158-536 mg/l, the range number of faucal bacterial colon was 21-495 CFU/100ml. Water quality index values (WQI) for all study stations, the range was 47-67, these were classified between third (Fair) and fourth (Marginal) categories. Classification of stations was fair for the first station and marginal for the second and third stations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.315
Teacher spread0.284 · 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 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
Published2022
Admission routes1
Has abstractyes

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Same venueIRAQI JOURNAL OF AQUACULTURESame topicWater Quality and Pollution AssessmentFrench-language works237,207