Using three-dimensional, digital models of pterosaur skulls for the investigation of their relative bite forces and feeding styles
Bibliographic record
Abstract
Abstract Simple, three-dimensional, digital models of the crania and mandibles of 22 pterosaurs – 13 pterodactyloids and nine non-pterodactyloids (‘rhamphorhynchoids’) – were generated to investigate gross-level mechanical aspects of the skulls as they would related to feeding behaviour such as bite force and speed of jaw motions. The key parameter was the determination of second moments of area of the mid-muzzle region and the computation of the bending moment relative to the occiput. The shorter, stockier skulls of basal ‘rhamphorhynchoids’ were the strongest for their size in terms of potential resistance to dorso-ventral bending, and this finding correlates with their robust dentitions. More derived ‘rhamphorhynchoids’ showed the start of a trend towards weaker skulls, but faster jaw adduction was interpreted to be an adaptation for the snatching of small prey. Pterodactyloids continued the trend to lengthen the skull and to reduce its cross-sectional area, resulting in less stiff skulls, but more rapid opening and closing of the jaws. Changes in the rear of the skulls and the development of coronoid eminences on the mandibles of all the pterodactyloids are correlated with the reduction in bite force and a concomitant increase in jaw closing speed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".