Bibliographic record
Abstract
An asymptomatic 43-year-old woman was recalled from a baseline screening mammogram for extensive bilateral retroareolar linear branching calcifications extending into the nipples (Figure 1). The patient also had normal-appearing retro-pectoral bilateral silicone implants (not shown). When the patient returned for diagnostic breast US, she reported that she had an injection of hyaluronic acid into her nipples performed 2 years ago for cosmesis. Targeted breast US demonstrated scattered calcifications with mildly prominent ducts in the subareolar regions bilaterally (Figure 2). The bilateral calcifications were assessed as benign given the clinical history of bilateral injections and the absence of other significant or suspicious imaging findings. Similar mammographic calcifications after hyaluronic acid nipple injections were described in a case report by Dow and Molleran (1). The use of hyaluronic acid–based fillers for enhanced nipple-areolar complex projection is a relatively new procedure (2). An injectable filler more typically used for facial cosmesis is utilized with the goal of increased nipple fullness. There has been a recent increase in interest in this technique since its use by celebrities has been promoted in the mainstream media. Breast radiologists should be aware of the breast imaging appearance after these injections to avoid unnecessary interventions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".