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Record W3120258552 · doi:10.3390/ani11010118

Changes in Behaviour and Voluntary Physical Activity Exhibited by Sled Dogs throughout Incremental Exercise Conditioning and Intermittent Rest Days

2021· article· en· W3120258552 on OpenAlexafffund
Eve Robinson, Emma Thornton, James R Templeman, Candace Croney, Lee Niel, Anna K. Shoveller

Bibliographic record

VenueAnimals · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Guelph
FundersMitacs
KeywordsConditioningSittingTurnoverMedicinePhysical therapyJumpingRest (music)Repeated measures designPhysical medicine and rehabilitationInternal medicinePhysiology

Abstract

fetched live from OpenAlex

Participation in repetitive endurance training decreases sled dogs’ voluntary activity and locomotive behaviours; however, the changes in their voluntary physical activity over consecutive rest days has not been examined to assess exercise-recovery. The objective of this study was to examine the changes in behaviour and voluntary activity of sled dogs throughout repetitive incremental conditioning and intermittent rest days. Fourteen dogs (6 males, 8 females; age 3.7 ± 2.7 years; BW 21.5 ± 2.8 kg) underwent 10 weeks of conditioning. Once a week, 5-min video recordings were taken pre- and post-exercise to measure the time spent performing agonistic behaviours, chewing on the gangline, digging, jumping, lunging, posture changing, sitting, standing and lying. Additionally, voluntary physical activity was measured on a day with an exercise bout during baseline, week 4, 5 and 7 and two consecutive rest days during baseline, week 1, 4, 5 and 7. A repeated-measures mixed model was used to analyse data in SAS (v 9.4.). As dogs progressed through their conditioning, the time spent changing posture prior to an exercise bout decreased (p < 0.05), suggesting that dogs may reduce their voluntary locomotive behaviours with increasing exercise. Additionally, dogs were more active during the second consecutive rest day than the first (p < 0.05), suggesting that rest days may provide a short-term recovery period.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.597

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.341
Teacher spread0.322 · 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 designBench or experimental
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

Citations3
Published2021
Admission routes2
Has abstractyes

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