Predatory behaviour of carnivorous dinosaurs: Ecological interpretations based on tooth marked dinosaur bones and wear patterns of theropod teeth.
Bibliographic record
Abstract
Predation marks on bones are a source on information on the feeding behaviour of the carnivores involved. Although predator damaged bone is common in the fossil record, published reports of such marks on dinosaur bones are rare. Patterns of bone modification by mammalian carnivores overlap patterns left by theropod dinosaurs.Differences in tooth morphology can also be correlated with characteristics of the marks left by the teeth. In a study of tooth marks on dinosaur bones from the Dinosaur Park Formation of Alberta, Canada, it was possible to identify the feeding theropods to family, generic and even species level. This was done by observing morphological differences between the teeth and jaws of theropod taxa. Denticle shapes, the distances between adjacent denticles, and the distances between adjacent teeth in the jaws provide clues for the identification of tooth marks.Tyrannosaurid tooth marks are the easiest to identify because of their large size. Parallel tooth marks are separated by more than 9 mm, and serration marks are larger than 0.3 mm. Tyrannosaurid teeth were examined for wear patterns to determine how they behaved when they stuck bone.The distributions of tooth marks amongst different taxa and different skeletal elements produced some interesting results. The frequency of tooth marked dinosaur bones is higher than expected. Up to 14 % of the observed hadrosaur bones were predator damaged. The lower incidence of damage in ceratopsian bones can be explained by the fact that the majority of ceratopsian bones were collected from mass death sites where there would have been an overabundance of food. Tyrannosaurids had a varied diet, and left their tooth marks on hadrosaur, ceratopsian, velociraptorine, and tyrannosaurid bones.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".