Explaining Dioscorides' “Double Difference”: Why Are Some Mushrooms Poisonous, and Do They Signal Their Unprofitability?
Bibliographic record
Abstract
The adaptive significance of toxins in mushrooms has received very little consideration, although it is clear that poisons have appeared (and/or disappeared) many times in mushrooms' evolutionary history. One possibility is that poisons have evolved in some mushroom species to deter their consumption by would-be fungivores before spore dispersal. If this is so, then one might expect poisonous mushrooms to signal their unprofitability in some way. In this study, we have conducted the first formal analysis of the ecological and morphological traits associated with edible and poisonous mushrooms in North America and Europe. Poisonous mushrooms do not tend to be more colorful or aggregated than edible mushrooms, but they are more likely to exhibit distinctive odors even when phylogenetic relationships are accounted for. This raises the intriguing possibility that some poisonous species of mushrooms have evolved warning odors (and perhaps tastes) to enhance avoidance learning by fungivores.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".