Bibliographic record
Abstract
The need for vitamin D to prevent rickets was the drive for selection of lighter skin color in temperate climates. Anthropologists also know that as human populations developed more sedentary lifestyles, this coincided with a decline in bone quantity, quality, and fracture resistance. Since osteoporosis occurs after the reproductive years, there is no way that natural selection could have adapted our biology to prevent it. However, osteoporosis can be largely prevented by optimizing physical activity, and the vitamin D-related factors of environment, and nutrition. The role of vitamin D3 in osteoporosis is conclusively established from a very simple meta-analysis of the four randomized, placebo-controlled clinical trials into the effect of 20 microg (800 IU) per day. These have all demonstrated that this dose prevents approximately 30% of hip or non-vertebral fractures compared to placebo, in adults older than 65 years. Intakes less than this have never been found effective. The lowest average serum 25-hydroxyvitamin D concentration in any study demonstrating fracture reduction was 74 nmol/L. Thus, 25-hydroxyvitamin D levels in older adults should exceed this amount. The role of vitamin D supplementation is to provide humans with the nutrient in an amount closer to our species' biological norm. This amount of vitamin D results in the optimal function of many aspects of health, including balance and muscle strength that lessen the risk of fracture beyond what is possible via the quality and quantity of bone itself.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".