Bibliographic record
Abstract
Although it is intuitive that large mammals need more food than smaller ones, it is not so obvious that, relative to their body mass, larger mammals consume less than smaller ones. In fact, on a per kg basis, the resting metabolic rate of a mouse is some 50 times higher than that of an elephant. The fact that metabolism could not be proportional to the mass of the animal was suggested by Sarrus and Rameaux in 1838. The first indication that oxygen consumption (or other indices of metabolic rate, Y ) related to the animal body mass ( M ) according to an exponential of the type Y = a · Mb, where b was about 0.75, was presented by Max Kleiber in 1932. Two years later Samuel Brody had collected sufficient data to construct the first “mouse-to-elephant” metabolic curve. The physiological basis of the relationship has been the object of many hypotheses, often accompanied by a great deal of controversy. This historical essay traces the origin of the mouse-to-elephant metabolic function, recalling the earliest concepts of metabolism and its measurements to understand the body size dependency, which is still one of the most elusive phenomena in comparative physiology. A brief look at the metabolic scaling of nonmammalian organisms will be included to frame the mouse-to-elephant curve into a broader context and to introduce some interesting interpretations of the mammalian function. © 2023 American Physiological Society. Compr Physiol 13:4513-4558, 2023.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".