Asymmetric breast enlargement minus central venous thrombosis in a hemodialysis patient
Bibliographic record
Abstract
A 76-year-old woman hemodialysis patient was hospitalized for community-acquired pneumonia complicating chronic obstructive pulmonary disease. End-stage renal disease secondary to hypertension had been diagnosed at the age of 64 for which the patient was initiated on maintenance hemodialysis. Then, she received a deceased donor kidney transplant at the age of 68 that succumbed to chronic rejection 4 years later when she was restarted on hemodialysis. Hemodialysis was performed via a right subclavian vein double lumen catheter for 2 months when a right brachio-axillary graft was inserted. Severe venous congestion, swelling, and nipple tenderness of her right breast noted on admission had been increasing for 6 weeks before hospital admission. No arm swelling was evident. Initial management of the patient's pneumonia and chronic obstructive pulmonary disease consisted of intravenous ceftriaxone and albuterol inhaler to which intravenous oxacillin (1 g q 6 hr) was added for presumed right mastitis. Radiological work-up for masses and malignancies was negative. An angiogram of the right upper extremity detected stenosis of the dialysis access graft at its anastomosis with the axillary vein. Angioplasty of the stenosis was performed without incident or evidence of central vein stenosis. Rapid resolution over 10 days of the unilateral breast congestion followed without complication.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".