Bibliographic record
Abstract
Abstract Reconstructing patterns of macroevolution has become a central endeavor in paleobiology, because it offers insight into evolutionary models shaping the history of life. As the most diverse and abundant animals since the Cambrian period, arthropods provide copious data to elucidate the emergence of body plans in metazoan lineages. However, information provided by fossils on the tempo and mode of this phenomenon has lacked a recent synthesis. Here, I investigate macroevolutionary patterns of morphological evolution in Euarthropoda using a combined extinct and extant dataset optimized for multivariate analyses. Overall ordination patterns between the main morphogroups are consistent with another, independently coded, extant-only dataset providing molecular and morphological rates of evolution. Based on a “deep split” phylogenetic framework, total-group Mandibulata and Arachnomorpha emerge as directional morphoanatomical lineages, with basal fossil morphogroups showing heterogeneously spread-out occupations of the morphospace. In addition to a more homogeneous morphological variation, new morphogroups arose by successive reductions of translation distances; this pattern was interrupted only by terrestrialization events and the origin of pancrustaceans. A displaced optimum type of model is proposed to explain the fast assembly of canalized body plans during the Cambrian, with basal fossil morphogroups fitting intermediate fitness peaks in a moving adaptive landscape. Given time constraints imposed by the paleontological evidence, and owing to the interplay between canalization and modularity, as well as a decoupling between molecular and morphological rates, the rise of euarthropods would support the view that the swiftness of the Cambrian explosion was mostly associated with the buildup of genetic regulatory networks.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".