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Record W3013359955 · doi:10.5430/ijba.v11n2p17

The Biodiesel Economic Indicators in Northern Brazil Based on Tocantins State

2020· article· en· W3013359955 on OpenAlexvenueno aff
Fernando Silva Lima, Waldecy Rodrigues, Nilton Marques de Oliveira

Bibliographic record

VenueInternational Journal of Business Administration · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicRural Development and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)BiodieselAgency (philosophy)Biodiesel productionBiofuelRelation (database)BusinessEconomicsEnvironmental scienceEcologyMicroeconomics

Abstract

fetched live from OpenAlex

This article aimed to perform a regional analysis of biofuel through the biodiesel production capacity in Tocantins in 2008 and 2017. The guiding question of this research was: what is the importance of the biodiesel sector in Brazil and Tocantins, in relation to the sectors of services, industry and storage services in terms of production capacity. The hypothesis is that, in relation to production capacity, the Tocantins biodiesel sector has lost its potential compared to other economic sectors in the state. Taking as theoretical assumption the theories of regional development. Data were collected from the website of the Brazilian Institute of Geography and Statistics (IBGE) and the National Petroleum Agency (ANP). The results show that biodiesel in 2008 had potential for Tocantins economy, but not in the same proportionality in 2017.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.185

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 head0.007
GPT teacher head0.221
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 designObservational
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
Published2020
Admission routes1
Has abstractyes

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