Eastern Newt (<i>Notophthalmus viridescens</i>) larvae alter morphological but not chemical defenses in response to predator cues
Bibliographic record
Abstract
Prey traits are often modified in response to exposure to predators, a phenomenon known as predator-induced phenotypic plasticity. Morphological plasticity in response to predator cues is well documented in amphibians; however, predator-induced chemical defenses have received relatively little attention. The Eastern Newt (Notophthalmus viridescens (Rafinesque, 1820)), which possesses tetrodotoxin—a toxin for chemical defense, is most vulnerable to predation during its larval stage. We assessed whether exposing Eastern Newt larvae to predator scent cues (from dragonfly larvae) would elicit change in their morphological and chemical defenses. Newt larvae exposed to scent cues of predatory dragonfly larvae exhibited significantly greater tail depths, which should increase survival of attempted predation by allowing them to swim faster, but did not differ in mass, snout–vent length, or tail length. Toxin concentrations in newt larvae were not significantly affected by exposure to these predator cues. Larval toxicity may be derived maternally or environmentally and is inflexible, or induced toxicity may only be detectable later in development. Predator-induced phenotypic plasticity, especially of chemical defenses, warrants greater attention, as potentially important outcomes of species interactions remain unclear.
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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) | 0.000 | 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".