Enriquecimento ambiental alimentar para gatos domésticos (Felis silvestris catus): aplicações para o bem-estar felino
Bibliographic record
Abstract
Provide favorable conditions for animals housed in restricted environments requires knowledge of species-typical behaviors in question.The poor literature, it provides less information about colonies of domestic cats (Felis silvestris catus), in confinement, leading to a deficit in quality of life and welfare of these animals under these conditions.This study aimed to analyze, through observation of exploratory behavior, feeding, individual differences and human contact with a known as a colony of 35 cats from a shelter behaves during daily diet (dry food prepared at the feeder), and in relation interaction with an environmental enrichment food (beef suspended from a steel cable).The results showed that animals possess both an organization for the daily diet and to the use of the gain, showing the existence of an ordering for the use of a resource.The data also revealed the presence of human influenced by food intake in animals.Based on the information contained in this paper emphasize that providing satisfactory housing, food and environmental enrichments for groups of animals, requires knowledge of the needs of the species, in this conditions, as well as the dynamics of resource use.
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 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 | 0.000 |
| 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) | 0.002 | 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".