Mastektomie bei Patientinnen mit BRCA-Mutation und Ovarialkarzinom sinnvoll?
Bibliographic record
Abstract
McGee J et al. Risk of breast cancer after a diagnosis of ovarian cancer in BRCA mutation carriers: Is preventive mastectomy warranted? Gynecol Oncol 2017; 145: 346 – 351 Für Frauen mit einer ererbten BRCA1- oder BRCA2-Mutation besteht ein erhöhtes Risiko, an Brust-, Eileiter- oder Eierstockkrebs zu erkranken. In der Provinz Ontario/Kanada erhalten Frauen mit einer solchen Mutation die Möglichkeit, sich einem intensivierten Brustscreening oder einer prophylaktischen Mastektomie zu unterziehen. J. McGee et al. haben nun untersucht, ob Mutationsträgerinnen mit Ovarialkarzinom von diesen Maßnahmen profitieren.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".