TRANSITION RATES BETWEEN SPECIALIZATION AND GENERALIZATION IN PHYTOPHAGOUS INSECTS
Bibliographic record
Abstract
Although most species of animals exhibit specialized patterns of resource use, it is unclear whether specialization evolves at a faster rate than generalization. To test this hypothesis, transition rates toward specialization and toward generalization were estimated using phylogenies from 15 groups of phytophagous insects. Among the groups studied, maximum-likelihood analyses showed that the forward transition rate from generalization to specialization was significantly higher than the reverse transition rate from specialization to generalization (mean ratio of forward to reverse transition rate = 1.47 using uniform branch lengths and 1.76 using Grafen branch lengths). Although phylogenetic conservatism of host-plant use is common, the results suggest that the evolution of specialization is a highly dynamic process. For example, higher transitions rates both toward and away from specialization as well as equal transition rates were inferred. Collectively, the results reveal a tendency for directional evolution toward increased specialization but also indicate that specialization does not always represent an evolutionary dead-end that strongly limits further evolution.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".