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Record W1964725496 · doi:10.1136/vr.100524

Number of cats and dogs in UK welfare organisations

2012· article· en· W1964725496 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.

Bibliographic record

VenueVeterinary Record · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsCATSWelfareAnimal welfareVeterinary medicineMedicineBiologyPolitical scienceInternal medicineEcologyLaw

Abstract

fetched live from OpenAlex

It is not known how many cats and dogs are admitted to welfare organisations annually. This study produced the first estimates of the size of this population. A questionnaire was mailed out to welfare organisations during 2010, followed by a postal/email reminder and requests to non-responders for a telephone interview. The questionnaire covered areas including, the current number of cats and dogs being housed, how much of the year organisations were operating at full capacity as well as the number of cats and dogs admitted, rehomed and euthanased between January and December 2009. Responses were obtained from 54.8 per cent of organisations. Sixty-six per cent of cat welfare organisations and 48 per cent of dog welfare organisations reported that they operated at full capacity for 12 months of the year. The number of cats and dogs entering UK welfare organisations during 2009 was estimated as 131,070 and 129,743, respectively. This highlights the scale of the work performed by welfare organisations in caring for and rehoming unwanted cats and dogs annually and emphasises the urgent need to address concerns over the considerable number of these animals. This study has also produced useful baseline data, which will be essential for monitoring population changes over time.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.260

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)0.0000.000

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 head0.035
GPT teacher head0.359
Teacher spread0.323 · 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