Surgery in Ovarian Cancer—Brazilian Society of Surgical Oncology Consensus
Bibliographic record
Abstract
Surgical management in epithelial ovarian cancer (EOC) has a significant impact on overall survival (OS) and progression-free survival (PFS). The Brazilian Society of Surgical Oncology (BSSO) supported an expert-led task force for consensus: the best EOC surgery is provided by experienced and specialized trained surgeons in cancer centers. Laparoscopic or radiological staging can predict the possibility of complete cytoreduction (CC0) and help to reduce unnecessary laparotomies. Carcinomatosis and nodal extension should be evaluated at imaging. Multidisciplinary input is essential for determining the need for the selection of patients for surgery and adjuvant chemotherapy in patients with EOC. The BSSO proposes quality assurance criteria and the need for national consensus. Genetic counseling was deemed mandatory for all patients with EOC. This consensus states the final recommendations from BSSO for the management of EOC.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".