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Record W2997573527 · doi:10.21438/rbgas.061406

Panorama da energia eólica sob a perspectiva dos impactos ambientais no Brasil

2019· article· pt· W2997573527 on OpenAlexaff
Cristhian Carla Bueno de Albuquerque, Lucas Rodrigues Maciel, Silvana Nakamori, Talila Auler, Anderson Catapan

Bibliographic record

VenueRevista Brasileira de Gestão Ambiental e Sustentabilidade · 2019
Typearticle
Languagept
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsImpact
Fundersnot available
KeywordsPanoramaPolitical scienceHumanitiesPhilosophyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

A presente pesquisa objetiva traçar um panorama da energia eólica sob a perspectiva dos impactos ambientais no Brasil. Para tanto, se valeu de uma revisão sistemática, a partir de um processo estruturado de busca de trabalhos científicos junto ao Portal de Periódicos da Capes. A revisão sistemática permitiu aferir que, dentre os principais impactos abordados, estão os de natureza sonora, visual, de restrição na utilização do solo e na utilização dos terrenos, de acidentes com aves e de radiação eletromagnética. No entanto, foi possível identificar que há convergência de quase a totalidade das pesquisas no sentido de que as potencialidades e os impactos positivos da fonte eólica ainda a tornam um meio de produção sustentável e de baixo impacto, em que pese as externalidades negativas. O presente estudo permite aferir as lacunas existentes quando se fala em pesquisa de impacto ambiental da energia eólica no Brasil, bem como das formas de mitigação destes impactos.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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 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

Citations2
Published2019
Admission routes1
Has abstractyes

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