Validating a molecular clock for nudibranchs—No fossils to the rescue
Bibliographic record
Abstract
Abstract Time calibrated phylogenies are typically reconstructed with fossil information but for soft‐bodied marine invertebrates that lack hard parts, a fossil record is lacking. In these cases, biogeographic calibrations or the rates of divergence for related taxa are often used. Although nudibranch phylogenies have advanced with the input of molecular data, no study has derived a divergence rate for this diverse group of invertebrates. Here, we use an updated closure date for the Isthmus of Panama (2.8 Ma) to derive the first divergence rates for chromodorid nudibranchs using multigene data from a geminate pair with broad phylogeographic sampling. Examining the species Chromolaichma sedna (Marcus & Marcus, 1967), we uncover deep divergences among eastern Pacific and western Atlantic clades and we erect a new species designation for the latter (Chromolaichma hemera sp. nov.). Next, we discover extensive phylogeographic structure within C. hemera sp. nov. sensu lato, thereby refuting the hypothesis of a recent introduction. Lastly, we derive divergence rates for mitochondrial and nuclear loci that exceed known rates for other gastropods and we highlight significant rate heterogeneity both among markers and taxa. Together, these findings improve understanding of nudibranch systematics and provide rates useful to apply to divergence scenarios in this diverse group.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".