Menopause, Hormonal Changes and Osteoporosis among Women in Region of the Western Macedonia
Bibliographic record
Abstract
Menopause is known as the end of natural transition in a woman’s reproductive life. Otherwise, is the period when progesterone and estrogen production is significantly reduced. The ovaries forbid the cell production and woman loses the ability of getting pregnant. Menopause is defined a period after 12 months without a menstrual cycle or even more. Osteoporosis is defined as bone tissue disorder characterized by loss of bone mass and bone structure disorder, enabling increased risk for fracture and bone fracture in general. Osteoporosis is considered the most prevalent disease around the age of 50. The prevalence of this disease on the basis of the most pronounced gender is in females compared to males, respectively a ratio of 3:1 (WHO, 2010). It is known that loss of osteoarthritis occurring in women during premenopausal is related to estrogen deficiency and the lack of hormonal imaging character that occurs in women during menopause and premenopause. Status of vitamin D plays a key role in bone health and early prevention of vitamin D deficiency disorders of rakitis and osteomalacia are very important but may also have a low vitamin D implication bone loss, muscle weakness and reduced fractures in older people and these are very important in public health issues in terms of morbidity, quality of life and costs for health services.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".