Epidemiology of testicular cancer: An overview
Bibliographic record
Abstract
Testicular cancer is a rare disease, accounting for 1.1% of all malignant neoplasms in Canadian males. Despite the low overall incidence of testicular cancer, it is the most common malignancy among young men. The incidence rate of testicular cancer has been increasing since the middle of the 20th century in many western countries. However, the etiology of testicular cancer is not well understood. A search of the peer-reviewed literature was conducted to identify important articles for review and inclusion in this overview of the epidemiology of testicular cancer. Most of the established risk factors are related to early life events, including cryptorchidism, carcinoma in situ and in utero exposure to estrogens. Occupational, lifestyle, socioeconomic and other risk factors have demonstrated mixed associations with testicular cancer. Although there are few established risk factors for testicular cancer, some appear to be related to hormonal balance at various life stages. Lifestyle and occupational exposures occurring later in life may play a role in promoting the disease, although they are not likely involved in cancer initiation. In addition to summarizing the current epidemiologic evidence on risk factors for testicular cancer, we suggest future research directions that may elucidate the etiology of testicular cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".