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Record W2139968209 · doi:10.1136/vr.c6842

Evaluation of the status of canine hydrotherapy in the UK

2011· article· en· W2139968209 on OpenAlexaboutno aff
M. Waining, Iain S. Young, S. B. Williams

Bibliographic record

VenueVeterinary Record · 2011
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsHydrotherapyMedicineCruciate ligamentHip dysplasiaPhysical therapySurgeryAlternative medicinePathologyAnterior cruciate ligament

Abstract

fetched live from OpenAlex

To establish the current status of canine hydrotherapy in the UK and to ascertain information regarding the current use of hydrotherapy, a questionnaire was sent to 152 hydrotherapy centres throughout the UK, from which 89 responded. Hydrotherapy was found to be a rapidly growing business. Stand-alone centres were in existence; however, many centres were connected to other businesses, including boarding kennels and general practice veterinary surgeries. The dogs using the facility were mainly pedigree breeds, particularly labrador retrievers (30 per cent), and the most commonly encountered conditions were rupture of the cranial cruciate ligament (25 per cent), hip dysplasia (24 per cent) and osteoarthritis (18 per cent). The proportion of qualified versus unqualified staff varied between centres, highlighting a need for improved regulation of this aspect of the industry. However, all the dogs treated by the hydrotherapy centres surveyed were direct veterinary referrals, suggesting a good degree of professionalism in the field and a high regard for the benefits of hydrotherapy.

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)0.001
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.260
GPT teacher head0.367
Teacher spread0.106 · 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

Citations28
Published2011
Admission routes1
Has abstractyes

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