Body Size Overlap, Habitat Partitioning and Living Space Requirements of Terrestrial Vertebrate Predators: Implications for the Paleoecology of Large Theropod Dinosaurs
Bibliographic record
Abstract
Ecological studies of extant tetrapod predators indicate that morphologically similar species which coexist in the same habitats routinely reduce interspecific competition for food by regular spacing of body size. The biggest predator species in the assemblage often differ more from one another in size than the smallest species. When coexisting carnivore species do not differ greatly in size, they commonly show morphological differences related to prey handling that may reduce dietary overlap. If carnivore species are very similar in both size and morphology, competition is avoided by habitat partitioning. Two tyrannosaurid species from the late Campanian Dinosaur Park Formation of western Canada are similar in both size and morphology, suggesting that they were segregated on the basis of habitat and/or biogeographic province. However; consideration of the living-space requirements of predator species of such large body size suggests that this kind of spatial separation would only have been possible had tyrannosaurids been more like ectotherms than endotherms in their metabolic rates. Distribution of different large theropod species across different, and surprisingly small (for the size of the animals) portions of Mesozoic landscapes may also account for the remarkably high diversity of morphologically similar large theropods in other dinosaur faunas.
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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) | 0.002 | 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".