Position Statement on Defining and Standardizing an Oncoplastic Approach to Breast-Conserving Surgery in Canada
Bibliographic record
Abstract
Although mastectomy is an effective procedure, it can have a negative effect on body image, sense of attractiveness, and sexuality. As opposed to the combination of breast oncologic surgery and plastic surgery, whose primary focus is on replacing lost volume, breast-conserving oncoplastic surgery (ops) redistributes remaining breast tissue in a manner that requires vision, anatomic knowledge, and an appreciation of esthetics, symmetry, and breast function. Modern surgical treatment of breast cancer can be realized only with breast and plastic surgeons working together using oncoplastic techniques to deliver superior cosmetic and cancer outcomes alike. Using this collaborative approach, oncologic and plastic surgeons in Canada have a significant opportunity to improve the care of their breast cancer patients. We propose a tri-level classification for volume displacement procedures to act as a rubric for the training of general surgeons and oncologic breast surgeons in oncoplastic breast-conserving therapy techniques. It is our position that ops enhances outcomes for many women with breast cancer and should become part of the standard repertoire of procedures used by Canadian oncologic surgeons treating breast cancer.
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.009 | 0.005 |
| Research integrity | 0.031 | 0.024 |
| Insufficient payload (model declined to judge) | 0.007 | 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".