Allometry (scaling) of blood components in mammals: connection with economy of energy?
Bibliographic record
Abstract
Hematocrit (HCT), blood hemoglobin (HGB), and serum concentrations of 14 commonly measured serum constituents in mammals were extracted from 131 publications published within the last 35 years and then subjected to allometric study (Y = aWb, where Y is the characteristic studied, W is body mass, and b is the scaling exponent). HCT and HGB values decreased (b < 0; p < 0.001) with body mass (W), as did serum K+, glucose, triglycerides, and urea values. In contrast, serum total protein and creatinine values increased (b > 0; p < 0.02 and p < 0.001, respectively) with W. The associations of HCT, HGB, glucose, triglycerides, and urea values with W may be assumed to coincide with the well-known reduction of metabolic rate per unit mass with increasing W of mammals. The decrease in serum K+values (p < 0.001) has yet to be adequately explained. Despite the ratio of muscle mass and W being constant for large and small mammals, serum values of creatinine rose (b = 0.14; p < 0.0001) with W. This suggests increased phosphocreatine turnover in muscles with W, which in turn might be connected to the increased efficiency reported for leg muscles in larger animals and, conceivably, might affect the measurement of metabolic rate and hence its scaling in mammals.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".