Bibliographic record
Abstract
Ricklefs and O'Rourke compared the diversity of appearance (aspect diversity) in samples of moths attracted to ultraviolet lights in Colorado, Arizona, and Panama. The more species-rich Panamanian assemblage of moths exhibited proportionately greater diversity of color and form, which supported stronger frequency-dependent selection by predators to diversify the strategies that moths adopt to achieve crypsis in an ecological space composed of resting backgrounds. Comparable analyses of 15 additional samples obtained from Ecuador to Canada fail to support Ricklefs and O'Rourke's original result. In the present analysis, two measures of the volume of aspect space were unrelated to the number of species per sample and did not differ between temperate and tropical localities. Either frequency-dependent (apostatic) selection is not a powerful force in diversifying moth appearance, or it does not vary with latitude, or potential resting backgrounds and cryptic strategies are similarly constrained in temperate and tropical regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".