Perception de l'humain et processus émotionnels et cognitifs chez le porcelet : impact de l'expérience avec l'humain
Bibliographic record
Abstract
Humans are part of the environment of domestic animals and their impact on animal welfare is largely underestimated. This thesis focused on the human-animal relationship during the post-weaning period in pigs. This period has not been much studied in a context of human-animal relationship, although it is known to be associated with the development of social abilities. The first part of this thesis aimed at understanding some processes involved in the development of the perception of humans by weaned piglets, namely memory, recognition and generalisation. Results showed that weaned piglets are able to form a memory of a familiar human which persists at least 5 weeks. Moreover, piglets adapt their behaviour according to the movements (rough or gentle) of humans towards them. However, the addition of food rewards or physical stress does not amplify their behavioural responses. An unfamiliar handler is not perceived positively. In addition, familiarisation to a passive human is not sufficient to remove the fear of an approaching human, suggesting that piglets form a context-specific memory. Thereafter, it has been shown that piglets can discriminate and recognise familiar humans based on experience, although their reactions depend on numerous factors, including the consistency of the experience and the context of testing. It does not preclude that piglets are able to generalise their behavioural responses to unfamiliar humans and to form a general memory of humans. The second part of the thesis aimed at investigating the impact of the experience with humans on emotional states and cognitive abilities of weaned piglets. It has been demonstrated that the way humans behave with piglets modulates their emotional states. Piglets receiving positive interactions with humans develop a positive emotional state and are more optimistic. Fear of humans appears to be correlated with motivation to explore, a temperament trait helping animals in a learning task. Overall, it has been demonstrated that the nature of the contact given by humans plays a major role in the development of the perception of humans, but also influences emotional states and is linked with motivation of this young domestic animal to learn and adapt to its environment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".