The association between gout and the risk of urological cancers: A pooled analysis of population‐based studies
Bibliographic record
Abstract
Gout is a disorder of purine metabolism, and is characterized by inflammation and hyperuricemia, which are considered to be associated with carcinogenesis and anti-carcinogenesis, respectively.[1][2][3] Insofar as can be ascertained, both gout and hyperuricemia are conspicuously related to metabolic syndrome, which has been hypothesized to be associated with carcinogenesis.4 Some researchers argue that high serum uric acid levels are related to increased risk of cancer, although uric acid was thought to be protective in tumorigenesis because of its systemic antioxidant properties.4 Recent epidemiological studies report conflicting relationships between gout or gout therapy and the risk of urological cancers, even when analyzing the same databases.[1][2][3][5][6][7][8][9][10] Given these contradictory reports, we conducted this meta-analysis to elucidate the risk of urological cancers among individuals with gout.
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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 | 0.021 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.017 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".