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Record W4396239044 · doi:10.1002/cncy.22825

Is molecular testing of salivary gland FNA specimens ready for prime time?

2024· editorial· en· W4396239044 on OpenAlexaff
Marc Pusztaszeri

Bibliographic record

VenueCancer Cytopathology · 2024
Typeeditorial
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineSalivary glandFine-needle aspirationMalignancyPathologyBiopsy

Abstract

fetched live from OpenAlex

With improvements in the molecular characterization of salivary gland neoplasms, fine‐needle aspiration specimens, including smears and cell blocks, are amenable to molecular testing for defining alterations, providing a specific diagnosis in many cases, and guiding management in a preoperative setting. Molecular testing can be particularly beneficial and complementary when used within the framework of the Milan system, as the results can further refine the risk of malignancy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.030
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0050.005
Open science0.0030.001
Research integrity0.0150.028
Insufficient payload (model declined to judge)0.0040.006

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 head0.037
GPT teacher head0.349
Teacher spread0.313 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations2
Published2024
Admission routes1
Has abstractyes

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