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Record W4247871253 · doi:10.1520/stp49359s

Synthesis of Biodiesel from Tobacco and Waste Frying Oil Using Heterogeneous KHCO3/Al2O3 Catalyst

2011· book-chapter· en· W4247871253 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

VenueBiofuels · 2011
Typebook-chapter
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsQueen's University
Fundersnot available
KeywordsIn situTransformation (genetics)Selection (genetic algorithm)Phase (matter)Materials scienceBiologyComputer scienceChemistryArtificial intelligenceGenetics

Abstract

fetched live from OpenAlex

The transesterification of tobacco seed oil and used frying oil to methyl esters (biodiesel) was studied using potassium bicarbonate loaded on alumina as heterogeneous catalyst. Reaction parameters such as catalyst concentration, methanol to oil ratio, reaction time, and agitation speed on the conversion of tobacco seed and used frying oil were investigated. The catalyst loaded KHCO3 of 30 % m/m on Al2O3, after being calcined at 700°C for 6 h, was found to be the optimum catalyst. The quality of the methyl esters was tested according to the European standard EN 14214. The two types of biodiesel produced seemed to meet all the parameters of the European standard except the oxidation stability. In the case of used frying oil biodiesel, not only the oxidation stability was not met, but this biodiesel did not also meet the acid value and water content specifications.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.050
GPT teacher head0.218
Teacher spread0.169 · 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