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Record W4395066464 · doi:10.5430/ijba.v15n1p76

Evaluation of the Sustainability of Sugarcane Expansion in the State of Goiás

2024· article· en· W4395066464 on OpenAlexvenueno aff
Mateus R. Resende Oliveira, Antônio Pasqualetto, Jeferson de Castro Vieira, Sergio D. de Castro

Bibliographic record

VenueInternational Journal of Business Administration · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSugarcane Cultivation and Processing
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de Goiás
KeywordsSustainabilityState (computer science)Agricultural engineeringComputer scienceMathematicsBusinessAgroforestryEnvironmental scienceBiologyAlgorithmEngineeringEcology

Abstract

fetched live from OpenAlex

The expansion of sugarcane cultivation, and the development and modernization of the sugarcane sector, have contributed to the strengthening of Brazilian agribusiness, thereby contributing to the growth of the country's economy. Thus, it is necessary to adapt agricultural or agro-industrial activities so that the entire productive system has a positive impact on the environment and society. In this sense, the objective was to evaluate the sustainability of the expansion of sugarcane cultivation in the State of Goiás. The methodology was based on the application of the Sustainability Barometer-SB Method. Thus, subsidies were provided to create a portrait of the sustainability of the expansion of the culture in the state. The results indicated that the sector occupies a medium/intermediate position in relation to Sustainability according to SB. We conclude that the method has the potential to be an important tool in assessing the sustainability of the sugar-energy sector in Goiás.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.331
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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