Blood flow to long bones indicates activity metabolism in mammals, reptiles and dinosaurs
Bibliographic record
Abstract
The cross-sectional area of a nutrient foramen of a long bone is related to blood flow requirements of the internal bone cells that are essential for dynamic bone remodelling. Foramen area increases with body size in parallel among living mammals and non-varanid reptiles, but is significantly larger in mammals. An index of blood flow rate through the foramina is about 10 times higher in mammals than in reptiles, and even higher if differences in blood pressure are considered. The scaling of foramen size correlates well with maximum whole-body metabolic rate during exercise in mammals and reptiles, but less well with resting metabolic rate. This relates to the role of blood flow associated with bone remodelling during and following activity. Mammals and varanid lizards have much higher aerobic metabolic rates and exercise-induced bone remodelling than non-varanid reptiles. Foramen areas of 10 species of dinosaur from five taxonomic groups are generally larger than from mammals, indicating a routinely highly active and aerobic lifestyle. The simple measurement holds possibilities offers the possibility of assessing other groups of extinct and living vertebrates in relation to body size, behaviour and habitat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".