Brachiopod shell thickness links environment and evolution
Bibliographic record
Abstract
Abstract While it is well established that the shapes and sizes of shells are strongly phylogenetically controlled, little is known about the phylogenetic constraints on shell thickness. Yet, shell thickness is likely to be sensitive to environmental fluctuations and has the potential to illuminate environmental perturbations through deep time. Here we systematically quantify the thickness of the anterior brachiopod shell which protects the filtration chamber and is thus considered functionally homologous across higher taxa of brachiopods. Our data come from 66 genera and 10 different orders and shows well‐defined upper and lower boundaries of anterior shell thickness. For Ordovician and Silurian brachiopods we find significant order‐level differences and a trend of increasing shell thickness with water depth. Modern (Cenozoic) brachiopods, by comparison, fall into the lower half of observed shell thicknesses. Among Ordovician–Silurian brachiopods, older stocks commonly have thicker shells, and thick‐shelled taxa contributed more prominently to the Great Ordovician Biodiversification but suffered more severely during the Late Ordovician Mass Extinction. Our data highlight a significant reduction in maximum and minimum shell thickness following the Late Ordovician mass extinction. This points towards stronger selection pressure for energy‐efficient shell secretion during times of crisis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".