MétaCan
Menu
Back to cohort
Record W247007988

Green diesel from Fischer-Tropsch Synthesis: challenges and hurdles.

2007· article· en· W247007988 on OpenAlexaboutno aff
Nicolas Abatzoglou, Ajay K. Dalai, F. Gitzhofer, N.C. Markatos, Aikaterini Stamou, J. Beltrão, Τhomas Panagopoulos, C. Helmis, E. Stamatiou, A. Hatzopoulou, M. D. Carlos Antunes

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsnot available
Fundersnot available
KeywordsFischer–Tropsch processDiesel fuelRenewable energySyngasContext (archaeology)Vegetable oil refiningWaste managementRenewable fuelsFossil fuelBiogasEnvironmental scienceEngineeringBiodieselChemistry
DOInot available

Abstract

fetched live from OpenAlex

Abstract: Kyoto’s protocol respects the view that, within the context of worldwide preservation and improvement, the quality of life is impossible to maintain without bringing forward new and replacement technologies. Energy supply is perhaps the most significant contributing vector and it is, in consequence, intrinsically linked to nearly all environmental actions. Liquid fuels, such as diesel oil, for transportation and heating needs, are in the centre of these preoccupations. The Fischer-Tropsch Synthesis is an “old ” technology but it can be adapted for use with syngas, biosyngas or biogas, for the production of diesel oil. Such diesel fuel oil, when coming from renewable sources, such as “biomass”, is called “green diesel”. This present work outlines the actual status of the FTS technology and details the scientific challenges, and the technical hurdles, associated with the use of renewable feedstocks and the newly developed “nanometric catalysts”. A recently commenced Canadian R&D project in this technical area is also briefly presented.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.568

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 head0.024
GPT teacher head0.239
Teacher spread0.214 · 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 designBench or experimental
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

Citations6
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicCatalysts for Methane ReformingFrench-language works237,207