A summary of key findings about cancers and nutrition Cancer and Nutrition in New Zealand
Bibliographic record
Abstract
Cancer registrations have increased from 10,000 in 1986 to 16,000 in 1995, an increase of nearly 60 percent. Some of the increase, however, is due to changes in the Cancer Registry, which took effect in 1994. In 1997 cancers of the lung, large bowel, and prostate were responsible for most cancer deaths among men. For women, cancers of the breast, lung and large bowel were the most common causes of cancer deaths.1,2 Cancer is responsible for more than a quarter of all deaths in New Zealand and the number of new cases of some cancers is increasing. Breast Cancer In 1997, 620 women died as a result of breast cancer (an age-standardised rate of 23.2 deaths for every 100,000 people).2 Among the established risk factors for breast cancer is age, with 70 % of cases being in women over 50. Family history, early
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".