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Record W6888814678 · doi:10.22034/ijab.v12i4.2274

Evaluation of Tigris River water quality within Baghdad City using the CCME index for various purposes

2024· other· en· W6888814678 on OpenAlexaboutno aff

Bibliographic record

VenueInternational journal of aquatic biology · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTurbidityWater qualityIndex (typography)Hydrology (agriculture)Aquatic ecosystemTotal dissolved solidsIndex method

Abstract

fetched live from OpenAlex

This study evaluated the Tigris River's water quality in Baghdad City for four different purposes, including drinking water supply, aquatic life, and agricultural requirements using Canadian WQI. The evaluation is based on data collected over 2021 and 2022. The parameters of water temperature, turbidity, total dissolved solids, pH, DO, nitrate, nitrite, ammonia, phosphate, chloride, fluoride, magnesium, calcium, sulfate, sodium, magnesium hazard (MH), and sodium adsorption ratio (SAR) were measured for index CCME calculation. The results indicated that water temperature and turbidity are the variables that crossed standard guidelines for aquatic life protection, ranked within fair quality. In contrast, water temperature, turbidity, and TDS are the variables that exceeded the allowable levels for overall water quality, mainly ranked within a good class. For drinking water purposes, turbidity and Ca are among the parameters that fall outside the acceptable limits, rated between marginal and fair class.

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)0.010
metaresearch head score (Gemma)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.146
GPT teacher head0.440
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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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