MétaCan
Menu
Back to cohort
Record W4410714598 · doi:10.32492/nucleus.v4i1.4106

Evaluasi Performa Furnace EDC (Ethyl Dichloride) Cracker di VCM (Vinyl Chloride Monomer)-1 Plant

2025· article· en· W4410714598 on OpenAlexaff
Rohiman Ahmad Zulkipli, Rachmadi Rachmadi, Yusuf Muhammad

Bibliographic record

VenueNucleus Journal · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsVinyl chlorideMonomerChemistryChlorideNuclear chemistryOrganic chemistryWaste managementEngineeringPolymer

Abstract

fetched live from OpenAlex

Furnaces in the production of VCM (Vinyl Chloride Monomer) must be operated with optimal efficiency to maximize production and minimize the formation of impurities (coke). Furnace efficiency is evaluated based on the ratio of heat generated from fuel combustion to heat absorbed by the EDC (Ethyl Dichloride) fluid, and is a key indicator of operational feasibility. In addition, the pressure difference of the inlet convection and outlet radiant sections is used as an additional parameter, where an increase in this value reflects the accumulation of deposits in the tubes. If the efficiency drops below the minimum operating conditions or the pressure difference between the convection inlet and outlet radiant section exceeds 4 kg/cm2G, the furnace is considered unfit for operation and decoking must be performed, which will increase operating costs. During the 12 days of monitoring (measurement every 8 hours), the average efficiency was 85.370%, the highest value was 87.348%, and the lowest value was 83.764%. The efficiency values tended to fluctuate and were below the minimum operating condition (88.898%). This is due to changes in operating conditions and manual control. Therefore, although the pressure difference is still below the threshold of 4 kg/cm2G, the furnace is considered unfit for operation.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.233
Teacher spread0.222 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNucleus JournalSame topicManagement and Optimization TechniquesFrench-language works237,207