Ambidextrous ungulates have more flexible behaviour, bolder personalities and migrate less
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
Studies of wildlife have shown consistent individual variation in behavioural plasticity, which affects the rate of adaptation to changing environments. More flexible individuals may thus be more prone to habituation and conflict behaviour, but these applications of personality to wildlife management are little explored. Behavioural lateralization reflects cerebral specialization that may predict diverse expressions of behavioural plasticity. We recorded front-limb biases (i.e. handedness) in wild elk ( Cervus canadensis ), a species with facultative migration and high rates of habituation inside protected areas. Less lateralized elk responded more strongly to the application of aversive conditioning (predator-resembling chases by humans) by increasing their average flight response distances, but these same animals were also quicker to reduce their flight responses (i.e. habituate) when human approaches were benign. Greater laterality was correlated with, but not completely predicted by, bolder personalities, which we quantified via five correlated behavioural metrics. Lastly, lateralized elk were three times more likely to migrate, whereas less lateralized animals were similarly likely to remain near humans year-round. Lateralized behaviours can provide insight into behavioural flexibility enabling certain individuals to more quickly adapt to human-disturbed landscapes, and offer an especially productive arena for collaborative work by behaviourists, conservation biologists and wildlife managers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.006 | 0.003 |
| 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