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Record W2065587424 · doi:10.1080/15567030600817795

Towards Producing a Truly Green Biodiesel

2008· article· en· W2065587424 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

VenueEnergy Sources Part A Recovery Utilization and Environmental Effects · 2008
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBiodieselRaw materialBiodiesel productionRenewable energyVegetable oil refiningWaste managementRenewable fuelsDiesel fuelFossil fuelEnvironmental scienceVegetable oilProduction (economics)BiofuelBiochemical engineeringPulp and paper industryEngineeringChemistryCatalysisEconomicsFood scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The production of biodiesel has received considerable attention throughout the world in the past few years. As an alternative to petrodiesel, biodiesel is a renewable fuel that is derived from vegetable oils and animal fats. However, the existing biodiesel production process is neither completely “green” nor renewable because it utilizes fossil fuels, mainly natural gas as an input for methanol production. Also the catalysts currently in use are highly caustic and toxic. The purpose of this article is to propose a new concept that uses waste vegetable oil and non-edible plant oils as biodiesel feedstock and non-toxic, inexpensive, and natural catalysts that overcome the limitation of the existing process. The economic benefit of the proposed method is also discussed. The new concept will render the biodiesel production process truly green.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.751

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 head0.014
GPT teacher head0.182
Teacher spread0.168 · 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