Asymptomatic thoracic splenosis after thoracoabdominal trauma: establishing a diagnosis
Bibliographic record
Abstract
A 58-year-old male was referred for evaluation ofmultiple pulmonary nodules suspicious for malig-nancy. Thirty-five years earlier, he had beeninvolved in a motor vehicle crash and was diagnosedwith a fractured mandible, multiple left-sided ribfractures, a pulmonary laceration with left haemo-pneumothorax, ruptured left diaphragm with intra-thoracic stomach and splenic laceration. Afterinitial assessment and stabilization he underwentsplenectomy and repair of the left diaphragmaticlaceration. He recovered uneventfully from theseinjuriesandwasdischarged.Recently,hedevelopedan upper respiratory tract infection and received achest radiograph (CXR) as part of his investigations.Apical and basal pleural-based nodules were iden-tified CXR (Fig. 1) and further clarified by computedtomography (CT) scan of the chest (Fig. 2).Attempted image guided trans-thoracic aspirationof these lesions in a peripheral hospital was abortedbecause of fear of complications. Video assistedthoracoscopic surgery (VATS) biopsy of the lesionswas performed. Intra-operative frozen section con-
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".