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O conhecimento sobre morcegos (Chiroptera: Mammalia) do estado do Espírito Santo, sudeste do Brasil

2010· article· pt· W2163714315 on OpenAlexaboutno aff
Poliana Mendes, Thiago Bernardi Vieira, Monik Oprea, Silvia R. C. Lopes, Albert David Ditchfield, Marlon Zortéa

Bibliographic record

VenuePapéis Avulsos de Zoologia · 2010
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

A Ordem Chiroptera apresenta importância relevante na dinâmica dos ecossistemas, sendo a ordem de mamíferos com maior diversidade de hábitos de vida. Dentre os estados da região Sudeste do Brasil, o Espírito Santo é um dos mais carentes em relação ao conhecimento de morcegos. Este estudo sintetizou o estado do conhecimento sobre quirópteros gerado no Espírito Santo. Para isso, foram catalogados os morcegos depositados no Museu de Biologia Prof. Mello Leitão (MBML), no Laboratório de Estudos de Quirópteros da Universidade Federal do Espírito Santo (LABEQ), Museum of Vertebrate Zoology (MVZ), Royal Ontario Museum (ROM), American Museum of Natural History (AMNH) e University of Michigan Museum Zoology (UMMZ). Além disso, foi realizada uma busca por artigos publicados sobre morcegos do Espírito Santo. Foram revistos 49 artigos científicos, realizadas três teses de mestrado e 11 monografias. Considerando as coleções amostradas e artigos publicados totalizam-se 63 espécies de morcegos para o estado, provenientes de 37 dos 78 municípios do Espírito Santo. A maior riqueza de espécies de morcegos foi encontrada nos municípios de Linhares e Santa Teresa, o que é provavelmente reflexo da maior parte dos espécimes depositados nos museus também serem desses municípios. O Espírito Santo apresenta um grande potencial para se encontrar novas ocorrências de espécies, enfatizando a importância da realização de futuros estudos sobre morcegos no estado.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2010
Admission routes1
Has abstractyes

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