Shell geometry and habitat determination in extinct and extant turtles (Reptilia: Testudinata)
Bibliographic record
Abstract
A variety of means, including forelimb proportions and shell bone histology have been used to infer the paleoecology of extinct turtles. However, the height-to-width ratio of the shell (as a one-parameter shell model) has been dismissed because of its unreliability, and more complex aspects of shell geometry have generally been overlooked. Here we use a more reliable, three-parameter geometric model of the shell outline in anterior view as a means to assess turtle paleoecology. The accuracy of predictions of extant turtle ecology based on our three-parameter shell model is comparable to that derived from forelimb proportions when distinguishing between three ecological classes (terrestrial, semiaquatic, and aquatic). Higher accuracy is obtained when distinguishing between two classes (terrestrial and non-terrestrial), because the contours of aquatic and semiaquatic turtles are often very similar. Our model classifies Proterochersis robusta , a stem turtle from the Late Triassic of Germany, as non-terrestrial, and likely semiaquatic. Our method, combined with inferences based on limb proportions, indicates a diverse range of ecotypes represented by Late Triassic stem turtles. This implies that the ecological diversification of stem-group turtles may have been rapid, or that a substantial period of currently cryptic diversification preceded the first fossil appearance of the turtle stem lineage during the Late Triassic.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".