BREAST CANCER IN SLOVENIA: EPIDEMIOLOGY AND SCREENING
Bibliographic record
Abstract
Background. Breast is the most frequent cancer site in Slovenian female population. In the year 2000 there were 932 new breast cancer cases registered (91.2/100,000), the incidence is expected to increase in the next ten years. Primary prevention includes general recommendations for healthy life style, e.g. avoidance of obesity, diet, physical activity and moderate alcohol consumption. Randomised controlled trials conducted in the USA, Canada, Scotland and Sweden have shown that regular mammography, alone or in combination with clinical examination, is effective in reducing mortality for about 25% in women over the age of 50, and much less in younger population. However, mammography screening has several drawbacks, the major being its tendency towards false positive and false negative results with all their potential psychosocial consequences. High quality assurance and control, as well as effective and readily available diagnostics and treatment, all of which demand high investments, are indispensable for good results. Conclusions. In Slovenia there are standards for breast cancer screening units, but their implementation in every day’s work is still a problem. In any case, breast cancer control could be achieved only by combined efforts directed into primary prevention and early detection, as well as by improving availability of effective treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".