Use of hormonal replacement therapy after treatment of breast cancer
Bibliographic record
Abstract
OBJECTIVE: To review the use of hormonal replacement therapy (HRT) after treatment of breast cancer. OPTIONS: The effect and role of estrogens on breast cancer. OUTCOME: Improved health and quality of life for women with breast cancer. VALUES: References were collected through MEDLINE searches up to 2002. EVIDENCE: The level of evidence and quality of recommendations have been determined using the criteria described by the Canadian Task Force on the Periodic Health Examination. BENEFITS, HARMS, AND COSTS: Utilization of the information to make proper risk-benefit assessment of HRT use in women with breast cancer. RECOMMENDATIONS: 1. HRT after treatment of breast cancer has not been demonstrated to have an adverse impact on recurrence and mortality. (II-2B). 2. HRT is an option in postmenopausal women with previously treated breast cancer. (II-2B). 3. Prospective, randomized clinical trial results are needed. (III-A). VALIDATION: Recommendations were viewed and revised by the Breast Diseases Committee of the Society of Obstetricians and Gynaecologists of Canada (SOGC) and approved by the Executive and Council of the SOGC. SPONSOR: The Society of Obstetricians and Gynaecologists of Canada.
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".