Implant-associated anaplastic large cell lymphoma of the breast: Insight into a poorly understood disease
Bibliographic record
Abstract
Implant-associated anaplastic large cell lymphoma (ALCL) is the subject of much debate in the field of plastic surgery. Only a few published cases have been reported and the rarity of the disease may make proving causality exceedingly difficult. Despite this, it is of utmost importance that full attention be devoted to this subject to ensure the safety and well-being of patients. The authors report one new case of implant-associated ALCL that recently presented to their institution. Implant-associated ALCL is a poorly understood disease. It should likely be considered its own clinical entity and categorized into two subtypes: one presenting as a seroma and the other as a distinct mass or masses. When reported, only textured implants have been associated with ALCL. The United States Food and Drug Administration and American Society of Plastic Surgeons have initiated a registry and have collected critical data to gain further understanding of this disease.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".