Pulmonary Light and Heavy Chain Deposition Disease
Bibliographic record
Abstract
A 64-year-old man with a history of smoking and asbestos exposure was referred for an F-18 FDG PET/CT, to evaluate multiple growing lung nodules that had been found incidentally on prior chest CTs. The PET/CT showed multiple hypermetabolic nodules in both the lungs, with varying intensity of FDG uptake, raising the suspicion of multifocal malignancy. Wedge resections of the right lung were done to remove the 2 most hypermetabolic nodules, and histologic evaluation revealed pulmonary light and heavy chain deposition disease. A follow-up PET/CT performed 1 year later showed another slowly growing nodule in the left lung with a significant increase in F-18 FDG uptake. Only 22 cases of pulmonary light chain deposition disease have been reported in the literature. This is a report of F-18 FDG uptake in nodules of pulmonary light chain deposition disease. These nodules can grow in size and can show increased F-18 FDG uptake on follow-up studies, mimicking a growing lung malignancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".