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Record W1996551246 · doi:10.1139/z09-142

Seasonal patterns and influence of temperature on the daily activity of the diurnal neotropical rodent Necromys lasiurus

2010· article· en· W1996551246 on OpenAlexvenueno aff
Emerson Monteiro Vieira, Leandro Baumgarten, Gabriela Paise, Rafael Gustavo Becker

Bibliographic record

VenueCanadian Journal of Zoology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsDry seasonNocturnalDiel vertical migrationWet seasonBiologySunriseCrepuscularEcologyRelative humidityDiurnal temperature variationVegetation (pathology)GrasslandAnimal scienceAtmospheric sciencesGeography

Abstract

fetched live from OpenAlex

We investigated the relation between temperature and diel activity patterns of Necromys lasiurus (Lund, 1841) in 10 sites of open vegetation (grassland fields) in the Cerrado (savanna-like vegetation) of central Brazil. We used live traps equipped with timing devices during two trapping sessions: in the end of the dry season (session 1, October 2001) and in the wet season (session 2, January–February 2002). Necromys lasiurus is basically a diurnal rodent with more pronounced crepuscular and nocturnal activity in the dry season than in the wet season. Only in the wet season did we detect significant between-gender differences, with males being less active than females in the first hours after sunrise but more active between 0900 and 1200. There was no significant activity–temperature relation in the dry season, but in the wet season, both genders showed a positive relation between ambient temperature and activity. Individuals might be avoiding hot midday hours in the end of the dry season to minimize time exposure to a physiologically stressful condition caused by the joint action of high temperatures and extremely low relative humidity (<15%). In the rainy season, the high relative humidity (80%–90%) might allow the animals to show a positive relation between activity and ambient temperature.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.116
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

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

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 head0.208
Teacher spread0.201 · 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 teacher head, 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

Citations45
Published2010
Admission routes1
Has abstractyes

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