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Circular Economy Approach on Decarbonization by Repurposing Used Cooking Oil for Nickel Smelter – A Case Study of PT Megah Surya Pertiwi, Obi Island, North Maluku, Indonesia

2024· article· en· W4405170823 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2024
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsNickel Institute
Fundersnot available
KeywordsSmeltingRepurposingNickelEnvironmental scienceMetallurgyWaste managementMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Abstract This research was instigated by the world’s endeavours to fight dependency on fossil energy sources. While coal prevails as a beneficial energy source, countries worldwide have strived to reduce coal usage in the future under the Net Zero Emission Pledge. Questions linger on how to minimize coal usage, play down its impact on the environment, and maintain economic advantages. This quantitative study focused on the repurposing of used cooking oil for alternative energy sources at PT Megah Surya Pertiwi (PT MSP), the first downstream company of Harita Nickel that processes nickel saprolite ore to Ferronickel using the Rotary Kiln Electric Furnace (RKEF) technology in Obi Island, North Maluku, Indonesia. As the company’s employment grows, wastes, including used cooking oil (UCO), accumulate. The result showed that repurposing UCO in PT MSP has lowered the consumption of coal by 2,206 tons (7.53%), diverted 2,980 tCO2e indirect GHG emission (Scope 1), and saved the total cost up to IDR 1,408,231,332.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.569

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 communication0.0000.001
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 head0.012
GPT teacher head0.199
Teacher spread0.187 · 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