Bibliographic record
Abstract
To the Editor: The recent article reporting the cause of death in older men living in the United States after the diagnosis of prostate cancer between 1988 and 20021 was interesting. The information on comorbid diseases and underlying cause of death can provide important clues regarding the risk factors for prostate cancer. The primary risk factors for prostate cancer other than age are diet2 and low serum 25-hydroxyvitamin D (25(OH)D).3 Diet also plays an important role in many chronic diseases. The evidence for a beneficial role of vitamin D in reducing the risk of prostate cancer is generally strong at the time of diagnosis such as greater survival rates for diagnosis of prostate cancer in summer or fall rather than winter or spring in Norway.3 The findings in reference 1 regarding comorbid diseases also support a role of vitamin D in reducing the risk of prostate cancer. Low serum 25(OH)D in men has been found to be associated in observational studies with risk of heart attack,4 congestive heart failure,5 peripheral vascular disease,6 stroke,7 chronic obstructive pulmonary disease,8 and type 2 diabetes mellitus.9 The findings regarding cause of death also support the theory of a relationship between vitamin D and cancer, because low serum 25(OH)D is also a risk factor for many types of cancer, as determined in a number of ecological studies.10 Based on the highly probable beneficial role of vitamin D in reducing the risk of many types of chronic diseases, people diagnosed with prostate cancer should have their serum 25(OH)D level measured and then seek to increase the level to between 40 and 60 ng/mL. Doing so would reduce their risk of death from all causes.11 For each 1,000 IU/d of vitamin D, serum levels rise by approximately 10 ng/mL.12 Conflict of Interest: Funding received from the UV Foundation (McLean, VA), and the Vitamin D Society (Canada). Author Contribution: Dr Grant is the sole contributor. Sponsor's Role: None.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".