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Record W2079779603 · doi:10.1037/0735-7044.117.4.813

Locomotor activity rhythms in dogs vary with age and cognitive status.

2003· article· en· W2079779603 on OpenAlexaff
Christina T. Siwak, P. Dwight Tapp, Steven C. Zicker, Heather Murphey, Bruce A. Muggenburg, Elizabeth Head, Carl W. Cotman, Norton W. Milgram

Bibliographic record

VenueBehavioral Neuroscience · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Toronto
FundersNational Institute on Aging
KeywordsBeagleCircadian rhythmRhythmLocomotor activityPhysiologySunlightPhysical activityCognitionPsychologyAudiologyBiologyMedicineInternal medicineNeuroscienceEndocrinologyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Beagle dogs exhibited diurnal patterns of locomotor activity that varied as a function of age, cognitive status, and housing environment. Aged dogs housed in an indoor facility showed a delayed onset of activity following lights on and displayed shorter bouts of activity, with more rest periods during the day, compared with young dogs. Cognitively impaired aged dogs were more active and showed a delayed peak of activity compared with unimpaired aged dogs. Housing in continuous light did not disrupt activity rhythms. The effect of age was less prominent in dogs housed in an indoor/outdoor facility. This suggests that bright sunlight and natural light-dark transitions are better able to consolidate and synchronize the activity rhythms of the dogs.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.043
GPT teacher head0.369
Teacher spread0.326 · 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

Citations75
Published2003
Admission routes1
Has abstractyes

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