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Record W4411700171 · doi:10.18280/ijdne.200523

The Impact of Environmental Pollution on Oil-Contaminated Soil Properties and Its Improvement Using Biodiesel in the Dora Refinery Area

2025· article· en· W4411700171 on OpenAlexvenueno aff
Manar Falih Jassim Al-Khafagi, Reyam Naji Ajmi, Estabraq Mohammed Ati, Awatif Mahfouz Abdulmajeed

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2025
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsnot available
FundersMustansiriyah UniversityUniversity of Baghdad
KeywordsEnvironmental scienceRefineryPollutionBiodieselOil refineryEnvironmental pollutionContaminationWaste managementEnvironmental engineeringEnvironmental protectionEngineeringEcologyChemistry

Abstract

fetched live from OpenAlex

In this research, oil-polluted soil in the vicinity of the Dora refinery was focused on.Soil samples were collected at appropriate depths and analyzed for their physical and chemical properties to determine the degree of pollution.The analyses included pH, organic matter content, electrical conductivity, bulk density, moisture content, and soil texture measurements.GC-MS was utilized for the identification of petroleum organic compounds.Used cooking oil was utilized to produce biodiesel, which was subsequently applied to the contaminated soil at a 10% by weight.Corn seedlings (Zea mays) were subsequently sown in treated and untreated soils, and growth parameters-height, number of leaves, and dry biomass-were quantified.The results indicated significant improvements in soil quality and plant growth in treated soil compared to untreated soil, showing the efficiency of biodiesel as an environmentally friendly bioremediation process for enhancing oil-contaminated soil quality and promoting plant growth.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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