Salivary Gland Fine Needle Aspiration and Introduction of the Milan Reporting System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fine needle aspiration (FNA) is a well-established procedure for the diagnosis and management of salivary gland lesions despite challenges imposed by their diversity, complexity, and cytomorphologic overlap. Until recently, the reporting of salivary gland FNA specimens was inconsistent among different institutions throughout the world, leading to diagnostic confusion among pathologists and clinicians. In 2015, an international group of pathologists initiated the development of an evidence-based tiered classification system for reporting salivary gland FNA specimens designated the "Milan System for Reporting Salivary Gland Cytopathology" (MSRSGC) that culminated with the publication of the MSRSGC Atlas in February 2018. The MSRSGC consists of 6 diagnostic categories, which incorporate the morphologic heterogeneity and overlap among various non-neoplastic, benign, and malignant lesions of the salivary glands. In addition, each diagnostic category is associated with a risk of malignancy and management recommendations. The main goal of the MSRSGC is to improve communication between cytopathologists and treating clinicians, while also facilitating cytologic-histologic correlation, sharing of data from different laboratories for quality control, and research. Herein, we review the current status of salivary gland cytology and the role of MSRSGC in providing a framework for reporting salivary gland lesions.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it