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Record W2004672653 · doi:10.4061/2010/951708

Cause and Possible Treatments of Foot Lesions in Captive Syrian Hamsters (<i>Mesocricetus auratus</i>)

2010· article· en· W2004672653 on OpenAlexafffund
Mélisa Veillette, Julie Guitard, Stéphan G. Reebs

Bibliographic record

VenueVeterinary Medicine International · 2010
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of CanadaUniversité de Moncton
KeywordsMesocricetusSyrian hamstersMedicineFoot (prosody)Veterinary medicinePhysiologyHamsterInternal medicineArt

Abstract

fetched live from OpenAlex

Syrian hamsters (Mesocricetus auratus) run extensively in exercise wheels. This running may cause paw lesions. Three treatments of these wounds (topical application of vitamin E, wheel blocking, and a combination of both) were compared using both sexes. A pretreatment period with or without wheels lasted 15 days and the ensuing treatment period lasted 45 days. At the end of the pre-treatment period, none of the animals without wheels had paw wounds, whereas at least 75% of the females and 100% of the males with wheels did. Females had fewer and smaller wounds than males at this point. At the end of the treatment period, no effect of vitamin E could be discerned, but significant wound healing occurred after wheel blocking in both males and females. Wheel blocking is an easy way to prevent or treat paw wounds, but it presents problems in terms of animal welfare, as wheels are an important cage enrichment for hamsters.

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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.084
GPT teacher head0.382
Teacher spread0.298 · 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

Citations6
Published2010
Admission routes2
Has abstractyes

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