Learning on the blink: physiological predictors of adaptive learning in an equine model
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
Domestic horses are regularly expected to demonstrate behavioural flexibility, the ability to adapt to changing environments, such as different riders and handlers. On the other hand, safe and successful equestrian activities rely on the horse to give consistent responses to important commands, demonstrating cognitive control. Striatal dopamine is a neurotransmitter involved in learning and may be related to spontaneous eye blink rate. Physiological arousal is known to influence cognitive performance in humans, but little is known about the relationship between arousal and learning in domestic horses. The aim of this thesis was to investigate novel physiological predictors of learning performance in horses. The same cohort of horses were investigated in a series of cognitive tasks, designed to challenge various aspects of cognitive flexibility and cognitive control. Spontaneous eye blink rate, heart rate variability and eye temperature were measured throughout as possible predictors of learning performance. It was revealed that horses’ arousal state at baseline and during training reliably predicts cognitive performance. In addition, this thesis provided preliminary evidence that hemispheric activation may be observable through lateralised eye temperature changes Further, it was revealed that horses may have higher cognitive capabilities than previously thought. This thesis makes several novel contributions to knowledge about equine learning, cognition and welfare.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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