Predator classification by the sea pen <i>Ptilosarcus</i> <i>gurneyi</i> (Cnidaria): role of waterborne chemical cues and physical contact with predatory sea stars
Bibliographic record
Abstract
Using laboratory and field experiments we examined the defensive behaviour of the sea pen Ptilosarcus gurneyi (Gray) towards three species of sea stars representing three levels of predatory threat. In the laboratory we first quantified the behaviour of P. gurneyi following physical contact with the sea stars Dermasterias imbricata (specialist predator), Pycnopodia helianthoides (generalist predator), and Pisaster ochraceus (nonpredator). Whereas the majority (73%) of the sea pens rapidly burrowed into the sediment following contact with D. imbricata, their response to P. helianthoides was highly variable and only 23% exhibited burrowing. In contrast, the response of P. gurneyi to P. ochraceus was weak and similar to that elicited by contact with a glass rod (control). Also, whereas the majority of sea pens displayed colony-wide bioluminescent flashes towards D. imbricata and P. helianthoides, their responses to P. ochraceus and the control were weaker and more localized. We subsequently examined whether waterborne predator chemical cues alone could trigger the defensive responses of P. gurneyi to D. imbricata and P. helianthoides, using laboratory bioassays of varying stimulus intensity. Interestingly, although exposure to chemical cues from predatory sea stars did not elicit any defensive response in P. gurneyi, subsequent physical contact with these predators triggered complete burrowing. Field bioassays using SCUBA yielded similar results, as P. gurneyi did not respond to the proximity of predators but rather delayed its response until physical contact occurred. Our study thus provides the first experimental evidence of predator-classification abilities in cnidarians and suggests that physical contact with predatory sea stars is required to trigger defensive behaviours in P. gurneyi.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".