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Record W4220691385 · doi:10.18280/ijdne.170101

Mapping Research Trends in Publications Related to Bio-Jet Fuel: A Scientometric Review

2022· review· en· W4220691385 on OpenAlexvenueno aff
Donaji Jiménez-Islas, Miriam Edith Pérez-Romero, María de la Cruz del Río‐Rama, Martha Beatriz Flores-Romero

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2022
Typereview
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsJet fuelScopusAviation biofuelBiofuelWork (physics)CitationChinaRenewable energyProductivityEnvironmental scienceFossil fuelNatural resource economicsAgricultural economicsEngineeringComputer scienceLibrary scienceEconomicsWaste managementPolitical scienceBioenergyEconomic growthMechanical engineering

Abstract

fetched live from OpenAlex

It is a fact that society has increased the need for mobility throughout the world. In that regard, it has become aware of the problems associated with the use of fossil fuels such as jet-fuel. As alter-natives, the use of bio-jet fuel has been proposed, which is a biofuel that researchers have evaluated and developed as an environmentally friendly alternative. The development of research on the topic of biofuels has generated a growing number of alternatives in the methods, technologies and raw materials for the production of bio-jet fuel. In this work, a bibliometric study has been developed to analyze the evolution of publications, the contribution of authors, countries, in terms of citation productivity on the topic of bio-jet fuel. Scientific publications were searched in the Scopus database for the period 2001 to 2021. The results showed that the publications have grown exponentially in the last 10 years. The most influential institution and country are from China. “Renewable and Sustainable Energy Reviews” is the most cited journal in the field of bio-jet fuel. The growth rate of publications was estimated using the Gompertz model, the rate was 0.2232 y-1. Most of the documents were published in journals Q1.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0100.010
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.112
GPT teacher head0.403
Teacher spread0.291 · 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
GenreReview

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

Citations8
Published2022
Admission routes1
Has abstractyes

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Same venueInternational Journal of Design & Nature and EcodynamicsSame topicBiodiesel Production and ApplicationsFrench-language works237,207