MEMORANDUM FOR: Science Writers and Editors on the Journal Press List
Bibliographic record
Abstract
July 13, 2000 (EMBARGOED FOR RELEASE 4 P.M. EDT July 18) A new study has found that the curative potential of treating testicular cancer with radiation or chemotherapy far exceeds the small risk of leukemia associated with these treatments. Testicular cancer is curable in a large majority of cases. However, it is important to understand the treatment factors that contribute to the development of secondary leukemia, which has a high mortality rate. The results of a multinational study of leukemia in relation to therapy for testicular cancer are presented by Lois Travis, M.D., Sc.D., of the National Cancer Institute, and colleagues, in the July 19 issue of the Journal of the National Cancer Institute. A case–control investigation of secondary leukemia was undertaken within a group of 18,567 testicular cancer patients diagnosed between 1970 and 1993 and who survived at least 1 year. These patients were reported to population-based cancer registries in the United States, Canada, Denmark, The Netherlands, Sweden, and Finland. Of this large group of men, 36 developed leukemia, and each was matched with two or three control patients (a total of 106 controls) who had been treated for testicular cancer and had not developed leukemia.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.209 | 0.197 |
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".