Global determinants of prey naiveté to exotic predators
Bibliographic record
Abstract
Prey naiveté-the failure of prey to recognize novel predators as threats-is thought to exacerbate the impact that exotic predators exert on prey populations. Prey naiveté varies under the influence of eco-evolutionary mediating factors, such as biogeographic isolation and prey adaptation, although an overall quantification of their influence is lacking. We conducted a global meta-analysis to test the effects of several hypothesized mediating factors on the expression of prey naiveté. Prey were overall naive towards exotic predators in marine and freshwater systems but not in terrestrial systems. Prey naiveté was most pronounced towards exotic predators that did not have native congeneric relatives in the recipient community. Time since introduction was relevant, as prey naiveté declined with the number of generations since introduction; on average, around 200 generations may be required to erode naiveté sufficiently for prey to display antipredator behaviour towards exotic predators. Given that exotic predators are a major cause of extinction, the global predictors and trends of prey naiveté presented here can inform efforts to meet conservation targets.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".