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Record W2619424771 · doi:10.3390/ani7060044

Long Term Physiologic and Behavioural Effects of Housing Density and Environmental Resource Provision for Adult Male and Female Sprague Dawley Rats

2017· article· en· W2619424771 on OpenAlexaff
Christopher Pinelli, Francesco Leri, Patricia V. Turner

Bibliographic record

VenueAnimals · 2017
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Guelph
FundersAmerican Association for Laboratory Animal Science
KeywordsRodentEnvironmental enrichmentOpen fieldPhysiologyElevated plus mazeAdult maleMedicineInternal medicineEndocrinologyPsychologyAnxietyBiologyEcology

Abstract

fetched live from OpenAlex

There is considerable interest in refining laboratory rodent environments to promote animal well-being, as well as research reproducibility. Few studies have evaluated the long term impact of enhancing rodent environments with resources and additional cagemates. To that end, male and female Sprague Dawley (SD) rats were housed singly (n = 8/sex), in pairs (n = 16/sex), or in groups of four (n = 16/sex) for five months. Single and paired rats were housed in standard cages with a nylon chew toy, while group-housed rats were kept in double-wide cages with two PVC shelters and a nylon chew toy and were provided with food enrichment three times weekly. Animal behaviour, tests of anxiety (open field, elevated plus maze, and thermal nociception), and aspects of animal physiology (fecal corticoid levels, body weight, weekly food consumption, organ weights, and cerebral stress signaling peptide and receptor mRNA levels) were measured. Significant differences were noted, primarily in behavioural data, with sustained positive social interactions and engagement with environmental resources noted throughout the study. These results suggest that modest enhancements in the environment of both male and female SD rats may be beneficial to their well-being, while introducing minimal variation in other aspects of behavioural or physiologic responses.

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 score0.391
Threshold uncertainty score0.631

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 studies0.0010.000
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 head0.310
Teacher spread0.267 · 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

Citations23
Published2017
Admission routes1
Has abstractyes

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