Temperament in Domestic Cats: A Review of Proximate Mechanisms, Methods of Assessment, Its Effects on Human—Cat Relationships, and One Welfare
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.
Bibliographic record
Abstract
Temperament can be defined as interindividual differences in behavior that are stable over time and in different contexts. The terms 'personality', 'coping styles', and 'behavioral syndromes' have also been used to describe these interindividual differences. In this review, the main aspects of cat temperament research are summarized and discussed, based on 43 original research papers published between 1986 and 2020. We aimed to present current advances in cat temperament research and identify potential gaps in knowledge, as well as opportunities for future research. Proximate mechanisms, such as genetic bases of temperament, ontogenesis and developmental factors, physiological mechanisms, and relationships with morphology, were reviewed. Methods traditionally used to assess the temperament of cats might be classified based on the duration of procedures (short- vs. long-term measures) and the nature of data recordings (coding vs. rating methods). The structure of cat temperament is frequently described using a set of behavioral dimensions, primarily based on interindividual variations in cats' responses toward humans and conspecifics (e.g., friendliness, sociability, boldness, and aggressiveness). Finally, cats' temperaments have implications for human-animal interactions and the one welfare concept. Temperament assessment can also contribute to practical aspects, for example, the adoption of shelter cats.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 it