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Record W4285177761 · doi:10.21438/rbgas(2022)092131

As fronteiras entre homem-gado-floresta

2022· article· pt· W4285177761 on OpenAlexaff
Karla Sessin Dilascio, Tatiane Silva Sousa, Charles Borges Rossi

Bibliographic record

VenueRevista Brasileira de Gestão Ambiental e Sustentabilidade · 2022
Typearticle
Languagept
FieldHealth Professions
TopicIndigenous Health and Education
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsGeographySociologyHumanitiesArt

Abstract

fetched live from OpenAlex

O aumento da prática da pecuária em reservas extrativistas na Amazônia levanta preocupação quanto ao futuro destas áreas no cumprimento da função de proteger os meios de vida de comunidades extrativistas e de garantir a utilização e a sustentabilidade dos recursos naturais. Até que ponto a pecuária como prática pode influenciar a mudança do uso e ocupação destas áreas protegidas? Este artigo trata da relação multiespécie entre homem-gado em uma comunidade ribeirinha do Vale do Juruá. O artigo mobilizará dados empíricos sobre os hábitos alimentares, a criação do gado e a percepção sobre a floresta da Comunidade Periquito da Reserva Extrativista Riozinho da Liberdade. Ao pensar "junto" e "com" o artigo tenta compreender as fronteiras possíveis entre a tríade homem-gado-floresta.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.029
GPT teacher head0.351
Teacher spread0.321 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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