Case Report: SCOUT MD™ four reflector technology—enhancing accuracy in breast lesion isolation
Bibliographic record
Abstract
(DCIS) for surgical resection using multiple SCOUT reflectors in a 45-year-old woman with DCIS of the left breast. Lesional resection using SCOUT MD™'s four unique reflectors was completed with real-time feedback from the SCOUT probe, providing information on distance, depth, and orientation around the perimeter of the calcifications. Successful DCIS resection was confirmed by post-resection tomosynthesis imaging of the partial mastectomy specimen, and negative margins were achieved. The patient synchronously chose contralateral breast reduction to achieve symmetry with the ipsilateral oncoplastic reduction mastoplasty. Advancements in SCOUT MD™ technology provide for improved intraoperative precision in the dissection with the use of four unique reflectors, while maintaining optimal cosmetic results by minimizing the removal of normal tissue. We believe these technological advancements in breast tumor localization will reduce rates of re-excision and the need for additional surgical management.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".