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Record W2891654506 · doi:10.1016/s1018-3639(18)30788-8

Assessment of Used Motor Oil Recycling Opportunities in the United Arab Emirates

2004· article· en· W2891654506 on OpenAlexaff
Ahmad Hamad, Essam Al-Zubaidy, Muhammad E. Fayed

Bibliographic record

VenueJournal of King Saud University - Engineering Sciences · 2004
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMotor oilOil refineryGasolineMotor fuelRefining (metallurgy)Environmental scienceAutomotive industryFuel oilWaste managementBusinessEngineeringMetallurgyMaterials science

Abstract

fetched live from OpenAlex

The treating and refining of used motor oil in United Arab Emirates (UAE) to convert it to recyclable products are investigated. Opportunities to convert the used motor oil to environmentally friendly products are explored. Laboratory analysis of various classes of lubricating oils indicated that the refined recycled motor oil currently produced in UAE requires more stringent quality control to meet the characteristics of virgin motor oil. The analysis of laboratory tests showed that the acid-clay process is quite an efficient in metal contaminants removal from the used motor oil. Lead is found to be a major contaminant in the used motor oil, with concentration up to 1000 PPM. Its high concentration was related to the use of leaded gasoline as an automotive fuel in UAE. The economical assessment of this study showed that re-refining of the used motor oil can generate up to $7,000,000 in annual revenue for the UAE This study also revealed that in UAE, about 64% of the generated used motor oil is not reported.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.052
GPT teacher head0.250
Teacher spread0.198 · 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 designSimulation or modeling
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

Citations9
Published2004
Admission routes1
Has abstractyes

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