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Record W4416895955 · doi:10.5539/jsd.v19n1p44

Using DEMATEL to Draw a Sustainable Performance Model in the Ricinus Communis L. Production System, Bahia - Brazil

2025· article· W4416895955 on OpenAlexvenueno aff
Alexei Perez Velazquez

Bibliographic record

VenueJournal of Sustainable Development · 2025
Typearticle
Language
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRicinusProduction (economics)Supply chainSustainable productionRaw materialSustainable development

Abstract

fetched live from OpenAlex

The search for levels of competitiveness among the players in the supply chain is an indispensable condition for innovation in the production services system. One sector that has experienced this dynamic is the supply of energy raw materials for biofuel production. The aim of this study is to propose a relational model of the criteria for the sustainable performance of Common Ricinus L. producers in the region of Irecê - BA. By identifying a set of criteria, the study enables the analysis of multiple dimensions that represent the production system of Ricinus Communis L. The research methodology implemented in the study is based on structural interpretive modeling as a reference model for sustainable performance in supply chain actors. The method used to analyze the relationships and trends between the selected criteria of the Ricinus Communis L. production system was the DEMATEL method. The data used is the result of interviews conducted with experts on the oilseed production system in the Northeast of Brazil, with questions about the cultivation of Ricinus Communis L. Among the findings of this study is the definition of a relational model of the criteria and theoretical frameworks that represent sustainable performance in the supply of raw materials by Ricinus Communis L. for the generation of biodiesel.

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)0.022
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.007
Science and technology studies0.0030.000
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0000.001
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 head0.057
GPT teacher head0.343
Teacher spread0.286 · 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 designQualitative
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

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