Study Study on aggression in dogs in a public shelter
Bibliographic record
Abstract
Assessing the behavior of a dog in a shelter is extremely important because the type of behavior can tell us if the animal can be given up for adoption, to whom it can be given up for adoption, if it cannot be given up for adoption and in which direction improvements in behavior need to be made to get it safely given up for adoption. This study aimed to assess the behavior of dogs in a public dog shelter by how a dog behaves towards a person (examiner) in a sequence of situations and to determine the number of individuals who responded with aggression. The behavior test was developed by The Rottweiler Rescue Society (Ontario, Canada) and John Rogerson, Blue Cross, Britain. Following minor modifications, has been used to examine dogs in public shelters. The test contains two additional assessment items from the article "An Evaluation of a Behavior Assessment to Determine the Suitability of Shelter Dogs for Rehoming" [1]. A total of 187 adult dogs were examined, of which 24 were identified with aggressive behavior and the types of aggression identified were dominance, interspecific, or territorial aggression. No behavioral test can show specifically how a dog will behave in a new environment, but the information obtained from the examination can indicate extreme manifestations of canine behavior, such as dominance aggression, possessive aggression, territorial aggression, and separation anxiety.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".