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Record W7128348167

Factors influencing how long a dog stays in a shelter

2016· dissertation· cs· W7128348167 on OpenAlexaboutno aff
Zdenka Průšová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2016
Typedissertation
Languagecs
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPurebredBreedGerman Shepherd DogPuppyPet therapy
DOInot available

Abstract

fetched live from OpenAlex

There were 1 643 dogs accepted to the dog shelter in Tábor in the years 20082015, wherein the amount of annualy accepted dogs slightly decreased. Dogs, that were returned to the original owner, spent shorter time (median 1 day) in the shelter than dogs, that were left alone and found a new home (median 18 days). The shelter accepted more male than female dogs. Simultaneously, male spent in the shelter longer time than female. Most of the dogs accepted to the shelter were younger than 1 year. The most common colour was black, the majority of dogs had a short and soft hair. Hybrids predominated among accepted dogs, following by German shepherds, Labrador retrievers and Dachshunds (or their hybrids). Dogs with a good character prevailed in the shelter. Data on abandoned dogs were statistically processed. There were found a significant effect of following variables on the length of stay in the shelter - age, height, purebred, temperament, colour, length and type of hair, and also the month of entry into the shelter. With increasing age and size (height) of dog there was demonstrably extended length of dogs stay in the shelter before they were adopted, as well as an aggressive character and dogs accepted in the shelter in October or November. Interestingly, the visually purebred dogs (corresponding to a certain breed standard) looked for a new home longer time than hybrids, provably. On the other hand, dogs with a light-coloured, soft or short hair and dogs accepted in February or April stayed in the shelter shorter time. When advertising the abandoned dogs for adoption, it is necessary to focus primarily on dogs that spend in the shelter longer time on average that means male dogs, large dogs, older dogs, dogs with long, black or rough hair and aggressive or temperamental dogs.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.300
Teacher spread0.287 · 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.

Study designBench or experimental
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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