Spatial distribution and population dynamics of free-roaming (stray and semi-domiciled) dogs in a major Brazilian city
Bibliographic record
Abstract
Introduction: Although estimate models have been proposed to determine free-roaming (both stray and semi-domiciled) dog populations, to date, no study has focused on the three major border areas of Brazil. Therefore, the present study assessed the free-roaming dog population of Foz do Iguaçu, a major far-west Brazilian city located in a three-border area (Brazil, Argentina, and Paraguay), which is considered among the top five Brazilian tourist destinations. Methods: Capture-release sampling was performed in three phases with a 6-month interval and 10-day duration of each phase, totaling 18 months, between 2018 and 2019. Results: , 95% CI). Of all free-roaming dogs, 452/1,125 (40.2%) were stray with no confirmed ownership or household, whereas 672/1,125 (59.8%) had a known origin, among which 625/1,125 (55.6%) were semi-domiciled with ownership or a household, 36/1,125 (3.2%) were neighborhood dogs with maintainers, and 11/1,125 (1.0%) were owned by recycling material collectors and homeless individuals. The majority of the 1,125 dogs (862/1,125; 76.6%) had an ideal body condition score. The high outdoor access of owned dogs is likely caused by cultural behavior. However, because 533/1,125 (47.4%) of the free-roaming dogs presented with clinical abnormalities, irresponsible ownership may have negatively impacted dog health and welfare. Discussion: This study was the first to establish the density of free-roaming dogs, the ratio of stray and semi-domiciled dogs, and their dynamics over time in Foz do Iguaçu. The findings may serve as a warning for the high level of dog outdoor access and irresponsible guardianship, which may negatively affect animal health and welfare, leading to diseases, accidents, trauma, and animal cruelty.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".