Middle Lobe Syndrome Due to Calcified Adenopathy
Bibliographic record
Abstract
Can Respir J Vol 21 No 4 July/August 2014 A 43-year-old nonsmoking man presented with a two-year history of recurrent respiratory infections. He had previously been given a clinical diagnosis of asthma. A review of systems was negative for aspiration, constitutional symptoms, occupational exposures and risk factors for tuberculosis and HIV. Spirometry demonstrated reduced forced expiratory volume in 1 s (78% predicted) without airflow limitation, and a methacholine challenge test was negative for asthma. Immunoglobulin levels and complete blood counts were normal. A chest radiograph (Figure 1) was abnormal, prompting a computed tomography (CT) scan of the thorax (Figures 2A and 2B). Bronchoscopic visualization of the right middle lobe bronchus revealed complete obstruction by inflamed bronchial mucosa and external compression. The hilar mass was identified and biopsied under endobronchial ultrasound guidance. A pathological review of biopsy specimens was negative for malignancy and revealed a mixed population of benign lymphocytes with no granulomas (Figures 3A and 3B). No mycobacteria were cultured. The patient was diagnosed with middle lobe syndrome (MLS) secondary to airway compression from an enlarged, partly calcified hilar lymph node, likely secondary to previous Histoplasma exposure given his residence in an endemic area. He was referred to thoracic surgery and scheduled for right middle lobectomy.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".