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Record W3094606432 · doi:10.7120/09627286.29.4.399

Evaluating factors influencing dog post-adoptive return in a Canadian animal shelter

2020· article· en· W3094606432 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAnimal Welfare · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAggressionAnimal welfareAnimal-assisted therapyHUBzeroCanisDemographyPsychologyAnxietyRisk factorPopulationMedicineEnvironmental healthPet therapyDevelopmental psychologyPsychiatryBiologyInternal medicineEcology

Abstract

fetched live from OpenAlex

Abstract Understanding the factors associated with post-adoptive return in dogs ( Canis familiaris ) is important for reducing shelter return rates. The objective of this retrospective study was to identify factors detectable in shelters associated with post-adoptive return in an objective dog-centric analysis. The records of 959 dogs were evaluated via factor analysis of seven behaviour and seven physical variables which resulted in the extraction of six principal factors. Fear aggression, ongoing health concerns, separation anxiety, sex-specific aggression, and age effect on source were not found to significantly impact outcome. In particular, dog aggression risk (a factor composed of breed, size, and dog aggression) was found to be significantly higher in returned dogs. Since dog aggression risk is associated with post-adoptive return, this could help shelters to modify policies to either screen aggressive dogs from the adoption population or improve adoption counselling in an attempt to help lower return rates.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.967

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 head0.040
GPT teacher head0.360
Teacher spread0.320 · 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