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Record W4388730801 · doi:10.1111/cyt.13331

Second edition of the Milan System for Reporting Salivary Gland Cytopathology: Refining the role of salivary gland <scp>FNA</scp>

2023· review· en· W4388730801 on OpenAlexaff
Esther Diana Rossi, Zubair Baloch, Güliz A. Barkan, Maria Pia Foschini, Daniel Kurtycz, Marc Pusztaszeri, Philippe Vielh, William C. Faquin

Bibliographic record

VenueCytopathology · 2023
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineCytopathologySalivary glandFine-needle aspirationPathologyMalignancyRadiologyGeneral surgeryCytologyBiopsy

Abstract

fetched live from OpenAlex

The use of standardised reporting systems for non-gynaecologic cytopathology has made enormous gains in popularity during the past decade, including for thyroid fine-needle aspiration, urine cytology, serous effusions, pancreas, lymph nodes, lung and more. In February 2018, the first edition of the Atlas of the Milan System for Reporting Salivary Gland Cytopathology (MSRSGC) was published. The MSRSGC defines six diagnostic fine-needle aspiration categories encompassing the spectrum of non-neoplastic, benign and malignant lesions of the salivary glands. The goal of the MSRSGC is to combine each diagnostic category with a defined risk of malignancy and a specific clinical and/or surgical management algorithm. Since its initial publication in 2018, more than 200 studies and commentaries have been published, confirming the role of the MSRSGC. The second edition of the MSRSGC, published in July 2023, includes refined risks of malignancy based on systematic reviews and meta-analyses, a new chapter summarising the use of salivary gland imaging, new advances in ancillary testing and updates in nomenclature.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.763
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.334
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations13
Published2023
Admission routes1
Has abstractyes

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