Bibliographic record
Abstract
CONSIDER THIS SCENARIO: A 35-year-old recently married woman is referred to a surgeon because of a growing breast lump. After a core biopsy shows cancer, she undergoes mastectomy for a 6-cm invasive lobular cancer that has spread to 8 axillary nodes. By the time she sees the medical oncologist, she is told that it is too late for a fertility consultation, and she receives a course of chemotherapy. At clinic appointments, she seems depressed and admits that her husband has been less supportive than she had hoped. After tamoxifen is started, treatment-related sexuality problems and the probability of infertility contribute to increasing strain on the couple's relationship. Their marriage ends two years after the woman's diagnosis.Six years after her diagnosis, this woman has completed all treatment, is disease-free, and is feeling extremely well physically. However, she is upset about being postmenopausal, and she is having difficulty adopting a child as a single woman with a history of breast cancer. Could this woman and her husband have been offered additional personalized interventions that might have helped them better cope with the breast cancer diagnosis and the effects of treatment?Compared with their older counterparts, young women with breast cancer often have greater and more complex supportive care needs. The present article describes the goals, achievements, and future plans of a specialized interdisciplinary program-the first of its kind in Canada-for women 40 years of age and younger newly diagnosed with breast cancer. The program was created to optimize the complex clinical care and support needs of this population, to promote research specifically targeting issues unique to young women, and to educate the public and health care professionals about early detection of breast cancer in young women and about the special needs of those women after their diagnosis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".