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Record W7081989908 · doi:10.11159/icepr25.187

Kuwait Environmental Remediation Program – Bioremediation of Oil-Contaminated Soil

2025· article· en· W7081989908 on OpenAlexvenueno aff

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsBioremediationEnvironmental remediationSoil contaminationSoil remediationContamination

Abstract

fetched live from OpenAlex

The Kuwait Environmental Remediation Program (KERP), established under the United Nations Compensation Commission (UNCC), addresses the restoration of oil-contaminated soil in the state of Kuwait in both the north and south oilfields.The North Kuwait Excavation, Transportation, and Remediation (NKETR) Project specifically handles the remediation of contaminated soil in the Raudhatain and Sabriya oilfields.This project endeavors to bioremediate 15.5 million cubic meters of contaminated soil burdened with total petroleum hydrocarbons (TPH) ranging from >1% to ≤5% using advanced landfarming technology.This paper highlights landfarming as the cornerstone bioremediation technology, crafted following the successful treatment of three out of forty-nine sections.Through proven methodologies, the study validates compliance with Remediation Target Criteria (RTC), ensuring sustainable contaminant treatment.Baseline and verification soil samples were analyzed in the laboratory, confirming oil degradation without rebound effects and affirming RTC attainment.This paper outlines sophisticated bioremediation technology, integrating precise water management, nutrient enrichment, and aeration techniques to optimize microbial activity and achieve enduring remediation of oilcontaminated soil.The NKETR project exemplifies a scalable model for environmental restoration, minimizing the use of landfills while maximizing eco-friendly treatment methodologies.This endeavor not only revitalizes Kuwait's landscapes but also establishes a robust framework for global remediation projects.Through scientific validation and strategic implementation, the project advances the frontier of bioremediation, offering insights for sustainable environmental stewardship.Through its commitment to ecological integrity, the NKETR transforms contaminated soil into vibrant ecosystems, rekindling the promise of Kuwait's golden sands and setting a precedent for worldwide environmental restoration efforts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes1
Has abstractno

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