Modularity promotes morphological divergence in ray-finned fishes
Why this work is in the frame
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Bibliographic record
Abstract
Modularity is considered a prerequisite for the evolvability of biological systems. This is because in theory, individual modules can follow quasi-independent evolutionary trajectories or evolve at different rates compared to other aspects of the organism. This may influence the potential of some modules to diverge, leading to differences in disparity. Here, we investigated this relationship between modularity, rates of morphological evolution and disparity using a phylogenetically diverse sample of ray-finned fishes. We compared the support for multiple hypotheses of evolutionary modularity and asked if the partitions delimited by the best-fitting models were also characterized by the highest evolutionary rate differentials. We found that an evolutionary module incorporating the dorsal, anal and paired fins was well supported by the data, and that this module evolves more rapidly and consequently generates more disparity than other modules. This suggests that modularity may indeed promote morphological disparity through differences in evolutionary rates across modules.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 it