Lateralized sleeping positions in domestic cats
Bibliographic record
Abstract
Both vertebrates and invertebrates show a multitude of left–right asymmetries of brains and behaviors 1 . For example, cats, dogs, and many other species have a preferred paw when handling food 2 . But why should humans and other animals have lateralized brains? Based on a large comparative approach 1 , it is likely that asymmetries serve several purposes. First, by specializing on one limb or one side of its sensory system, the contralateral hemisphere goes through life-long cycles of motor and perceptual learning, thereby increasing the speed of processing and motor efficacy, decreasing reaction time, and enhancing discrimination ability. Second, by having two complementary, specialized hemispheres, neural processes are computed in parallel, thereby reducing cognitive redundancy 1 . For example, the right hemisphere excels in processing threat-related stimuli, providing the left visual field an advantage in reacting to a predator approaching from the left 3 . Here, we report that two-thirds of cats prefer a leftward sleeping position, giving their left visual field and thus their right brain half a privileged view of approaching animals without being obstructed by their own body. Video abstract
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".