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Record W2143903070 · doi:10.1258/002367700780384681

Preferences of mice, <i>Mus musculus,</i> for different types of running wheel

2000· article· en· W2143903070 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLaboratory Animals · 2000
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMedical Research Council Canada
KeywordsWheel runningWire meshComputer mouseComputer scienceBiologyMaterials scienceEndocrinologyHuman–computer interaction

Abstract

fetched live from OpenAlex

Mice are increasingly used in research. In particular, their wheel running is often used as a measure of activity, and as a marker of phase of circadian rhythms. Learning about the preferences of mice for different types of wheel may improve their welfare and suggest ways of increasing activity levels. Mice, Mus musculus, were given a choice between different types of running wheel by putting them in cages equipped with two wheels. Strong preferences were shown for wheels with a plastic mesh flooring, rather than the standard metal rods only. The mesh was even preferred over a solid base, although this effect was not seen in mice that had been given access only to wheels with the solid base immediately prior to the choice test. Small diameter wheels, sometimes sold as mouse wheels, were preferred less than standard-sized wheels with rods. The results suggest that types of running wheel often used in laboratories can be improved by considering the animals' preferences. The types of wheel tested here are easy to maintain and entail little additional cost, while increasing the mouse's interest in running and exercise.

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.

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 score0.797
Threshold uncertainty score0.681

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)0.0010.000

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 head0.319
Teacher spread0.276 · 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