Accuracy of marker clip placement after mammotome breast biopsy.
Bibliographic record
Abstract
OBJECTIVE: To assess, after stereotaxic, vacuum-assisted breast biopsy, the accuracy of marker clip deployment for guiding subsequent needle localization procedures and surgery. METHODS: We conducted a retrospective review of 100 vacuum-assisted core breast biopsies that were followed by marker clip deployment. Craniocaudal (CC) and mediolateral oblique (MLO) mammograms were used to locate clips relative to the centre of the target lesion in 5-mm increments. RESULTS: In the 94 of 100 cases adequate for review, maximum marker clip displacement of less than 10 mm on either the CC or MLO views was observed in 68 (72%) cases. In 9 (10%) cases, the localization clip was positioned more that 24 mm from the target lesion. CONCLUSION: Post-biopsy CC and MLO radiographs are recommended to identify those cases in which there is a significant difference between the location of the marker clip and the biopsied lesion.
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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 | 0.003 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".