Climatic influences on basal metabolic rates among circumpolar populations
Bibliographic record
Abstract
This article examines evidence for elevations in basal metabolic rate (BMR) among indigenous Northern (circumpolar) populations and considers potential mechanisms and the adaptive basis for such elevations. Data on BMR among indigenous (n = 109 males; 122 females) and nonindigenous (n = 15 males; 22 females) circumpolar groups of North America and Siberia are compiled and compared to predicted BMRs based on three different references: body surface area (Consolazio et al., 1963), body mass (Schofield, 1985), and fat-free mass (Poehlman and Toth, 1995). Regardless of which reference is used, indigenous circumpolar groups show systematic and statistically significant elevations in BMR ranging from +7% to +19% above predicted values for indigenous men and from +3 to +17% for indigenous women. Nonindigenous males also show elevations in BMR, although not to the same extent as in indigenous men (deviations = +3 to +14%), whereas nonindigenous females show no clear evidence of elevated BMRs (deviations = -7 to +5%). This pattern of variation between indigenous and nonindigenous groups suggests that both functional and genetic factors play a role in metabolic adaptation to northern climes. Recent studies on the ecology and genetics of thyroid function offer insights into the mechanisms through which indigenous circumpolar populations may regulate metabolic rates. Studies of seasonal variation in thyroid hormone levels suggest that indigenous circumpolar populations may have a greater capacity to elevate BMR during severe cold than nonindigenous groups. Recent twin studies indicate a significant genetic component of thyroid responses to environmental stressors. Further research exploring the genetics of seasonal variation in thyroid function and BMR among circumpolar groups would advance understanding of the role that selection may have played in shaping metabolic variation.
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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 | 0.000 | 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) | 0.001 | 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".