Cadences of the collective: conspecific stimulation patterns interact with endogenous rhythms to cue socially mediated response shifts
Bibliographic record
Abstract
Many animals form behavioral collectives, and optimal interaction strategies often differ across social contexts. Sensory scenes generated by many interacting conspecifics are complex. Thus, maintaining socially calibrated responses requires individuals to distill key features from conspecific scenes to guide continued adjustments to social fluctuations. Túngara frogs produce mating calls in choruses varying in size, and interaction patterns differ across social environments; rivals alternate their calls in smaller choruses, but increasingly overlap one another's calls in a stereotyped fashion as chorus size increases. We used automated playback to investigate the cues guiding this socially mediated shift in interaction modes. We played conspecific stimulus calls to males at various delays relative to their own calls, preceded by various acoustic motifs that mimicked conspecific stimulation patterns males will hear in different social environments. Males almost never overlapped isolated stimulus calls at any delays. However, their probabilities of overlapping stimulus calls increased markedly when stimulus calls were preceded by motifs characteristic of larger choruses, i.e. those exhibiting intense conspecific stimulation patterns. Furthermore, the escalatory effects of motifs became increasingly pronounced as motif/stimulus combinations were played at later delays. Thus, interaction strategies are calibrated to current social dynamics each call cycle in response to a multifaceted cue that incorporates both the nature of conspecific stimulation experienced and how the timing of this stimulation interacts with endogenous responsiveness rhythms. Our results highlight that inactive phases within behavioral rhythms provide repeated opportunities to sample current social dynamics, allowing response patterns to be continually calibrated to social fluctuations in behavioral collectives.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".