“Cold” Spondylodiscitis on 18F-FDG PET/CT in a Patient With Myelofibrosis
Bibliographic record
Abstract
A 74-year-old man was evaluated by bone scan for possible rib fractures, which revealed a diffuse skeletal uptake secondary to myelofibrosis and focal midthoracic uptake. Chest CT and F-FDG PET/CT demonstrated pathological vertebral fractures of the midthoracic spine, which appeared as a cold defect on PET comparing to intense marrow uptake related to myelofibrosis and a lung nodule with a low uptake, later biopsy-proven as non-small cell lung carcinoma (NSCLC). MRI confirmed CT findings for the spine noting also an enhanced epidural collection. Biopsies did not reveal malignant cells. Final diagnosis was spondylodiscitis and a stage I NSCLC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".