Whiteflies And White Lies: Dan Gerling'S Speculation On Deceptive Communication In Parasitoid-Host Interactions
Bibliographic record
Abstract
We used game theory to assess speculation from the late Dan Gerling that whitefly hosts might evolve to exploit the chemosensory system of their parasitoid natural enemies via fake (pseudo) marking pheromones. We considered three scenarios. Scenario 1 assumed parasitoid response to hosts was non-evolvable and hardwired. Here, we found that pseudo-marking was a viable strategy; values at fixation depended upon costs and benefits of marking. Scenario 2 assumed parasitoid host acceptance was non-evolvable and plastic. Here, we found that strong fake marking was common when parasitism was moderate, that is when the risk was high but parasitoids would tend to reject because good hosts were available. Scenario 3 assumed plastic parasitoids that could co-evolve with the host. Here, we found parasitoid sensitivity to host marks, at the population level, never stabilized. By contrast, fake host marking did stabilize but only at high signal strength when levels of parasitism were intermediate (i.e. 30–40 %); when parasitism was more common, marks were ignored and hiding from enemies became more effective. We discuss the potential for evolution of pseudo-oviposition marks in the general sense with reference to sensory deception in non parasitoid-host systems.
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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 | 0.002 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".