Onsite evaluation of endoscopic ultrasound fine needle aspiration: the endosonographer, the cytotechnologist and the cytopathologist
Bibliographic record
Abstract
Endoscopic ultrasound guided fine needle aspiration (EUS-FNA) has become an essential tool in the management of multiple diseases. Its accuracy is related to different aspects of the technique, one of the most important being the experience and interaction of the endosonographer and pathologist. Certain studies over the past years have highlighted the importance of having rapid on-site evaluation (ROSE) of samples obtained at the time of EUS-FNA. We have reviewed the role of ROSE, performed by the same endosonographer, a cytotechnologist and an expert cytopathologist. The available data suggest that ROSE (either by the endosonographer, the cytotechnologist, or the cytopathologist) improves sample adequacy and diagnostic yield, with the best option to have ROSE performed by an expert cytopathologist. However, if non-ROSE accuracy is already very high, any improvement is harder to achieve.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".