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Record W2055154160 · doi:10.4141/cjas07125

Seasonal change of daily motor activity rhythms in <i>Capra hircus</i>

2008· article· en· W2055154160 on OpenAlexvenueno aff
Giuseppe Piccione, Claudia Giannetto, Stefania Casella, G. Caola

Bibliographic record

VenueCanadian Journal of Animal Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEffects of Environmental Stressors on Livestock
Canadian institutionsnot available
Fundersnot available
KeywordsSolsticephotoperiodismCapra hircusAnimal scienceActigraphyEquinoxMotor activityRhythmBiologyCircadian rhythmMedicineGeographyBotanyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

To evaluate if seasonal changes in photoperiod and temperature were associated with changes in total daily motor activity we recorded the total daily motor activity of five clinically healthy goats at four different times of the year (vernal equinox, summer solstice, autumn equinox and winter solstice). Goats were housed under natural photoperiod and natural ambient temperature in a 12-m 2 sound-proof box equipped with 50 × 100 cm opening window, which allowed natural ventilation. Total motor activity of each goat was recorded by Actiwatch-Mini ® , actigraphy-based data loggers that record a digitally integrated measure of motor activity. Our results show the existence of clear seasonal variations in daily activity rhythms in goats, with the highest daily amount of activity during the vernal equinox (769.21 ± 82.56 movements h -1 ) and the lowest during the winter solstice (401.65 ± 61.82 movements h -1 ) (P &lt; 0.0001). There was also a change in the amount of motor activity observed during photophase and scotophase through the year (P &lt; 0.0001). The cosine peak (times of the daily peaks), always occurred in the middle of the photoperiods and varied from season to season (P &lt; 0.0001). Our data indicate that daily motor activity of goats varies with season. Key words: Daily rhythm, environmental condition, total activity, goat

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.216
Teacher spread0.187 · 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

Citations19
Published2008
Admission routes1
Has abstractyes

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