The role of endobronchial ultrasound/esophageal ultrasound for evaluation of the mediastinum in lung cancer
Bibliographic record
Abstract
The introduction: of ultrasound-based, minimally invasive techniques (Endobronchial Ultrasound guided Transbronchial Needle Aspiration (EBUS-TBNA) and Esophageal Ultrasound guided Fine Needle Aspiration) has revolutionized care of patients with lung cancer needing mediastinal lymph node sampling. When combined, the techniques offer safe and accurate assessment of mediastinum, with accuracy surpassing that of the pervious gold standard - cervical mediastinoscopy. EBUS-TBNA can be used for mediastinal restaging in both, patients with suspected recurrence following treatment for primary lung cancer and followingneoadjuvant therapy in preparation for definitive surgical intervention. Both EBUS-TBNA and esophageal ultrasound guided fine needle aspiration techniques have been shown to provide sufficient material for molecular and DNA testing, extending their role beyond initial evaluation of the mediastinum to help direct and personalize medical treatment and predict response to therapy. In the future, assessing sonographic features of lymph nodesmay become useful in predicting nodal metastasis, further increasing the sensitivity of these techniques for detection of metastatic disease.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".