Do warning displays predict striking behavior in a viperid snake, the cottonmouth (Agkistrodon piscivorus)?
Bibliographic record
Abstract
Warning displays are defined as signals designed to intimidate predators or indicate a proclivity to fight. However, support for the idea that warning behaviors signal an intent to fight is largely based on anecdotes and isolated observations, and a complete understanding of antipredator behavior will only be achieved if specific hypotheses are experimentally tested. Herein, we tested in a North American viperid snake, the cottonmouth ( Agkistrodon piscivorus (Lacépède, 1789)), the hypothesis that warning displays serve as a reliable signal to potential predators that a snake will strike. The cottonmouth exhibits two stereotypical warning displays during predator confrontation, i.e., mouth gaping and tail vibrations, making it an ideal study organism to experimentally test the relationship between warning displays and defensive striking. To test this idea, we recorded the sequence of defensive behavior — gaping, tail vibrating, and striking — of cottonmouths towards a standardized predatory stimulus in the laboratory. As predicted, snakes that gaped during the trials were subsequently more likely to strike than snakes that did not. In contrast, striking behavior was independent of the occurrence of tail vibrations. Our results suggest that gaping behavior — but not tail-vibrating behavior — may provide an honest signal to would-be predators.
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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) | 0.001 | 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".