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Record W2740074804 · doi:10.1590/0103-8478cr20151216

Complementing firewood with alternative energy sources in Rio Pardo Watershed, Brazil

2017· article· en· W2740074804 on OpenAlexaff
Luana Dessbesell, Jorge Antônio de Farias, Fábio Roesch

Bibliographic record

VenueCiência Rural · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsLakehead University
FundersUniversidade Federal de Santa MariaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsFirewoodSawdustPelletsEnvironmental sciencePelletContext (archaeology)Pulp and paper industryAgroforestryWaste managementGeographyEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

ABSTRACT: Wood is the primary energy source for grains and Tobacco drying in the Rio Pardo Watershed (RPW). The amount of firewood produced in the RPW is not enough to supply the demand. Recently, an automatized supply system was introduced in the region enabling the use of sawdust and pellets. In this context, this study aims to compare firewood, sawdust and pellets as energy sources for Tobacco curing in air-forced curing systems. Energetic density was used to estimate the biomass consumption in Tobacco curing. The consumption of biomass is lower for pellet, followed by firewood and sawdust. Pellets and sawdust could complement firewood in the region; however, research is necessary to ascertain the economic feasibility.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.228
Teacher spread0.221 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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