An ecological approach to measuring synchronization abilities across the animal kingdom
Bibliographic record
Abstract
In this perspective paper, we focus on the study of synchronization abilities across the animal kingdom. We propose an ecological approach to studying nonhuman animal synchronization that begins from observations about when, how and why an animal might synchronize spontaneously with natural environmental rhythms. We discuss what we consider to be the most important, but thus far largely understudied, temporal, physical, perceptual and motivational constraints that must be taken into account when designing experiments to test synchronization in nonhuman animals. First and foremost, different species are likely to be sensitive to and therefore capable of synchronizing at different timescales. We also argue that it is fruitful to consider the latent flexibility of animal synchronization. Finally, we discuss the importance of an animal's motivational state for showcasing synchronization abilities. We demonstrate that the likelihood that an animal can successfully synchronize with an environmental rhythm is context-dependent and suggest that the list of species capable of synchronization is likely to grow when tested with ecologically honest, species-tuned experiments. This article is part of the theme issue 'Synchrony and rhythm interaction: from the brain to behavioural ecology'.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".