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Record W1971483095 · doi:10.1002/dc.20830

Diagnostic terminology and morphologic criteria for cytologic diagnosis of thyroid lesions: A synopsis of the National Cancer Institute Thyroid Fine‐Needle Aspiration State of the Science Conference

2008· article· en· W1971483095 on OpenAlexaff
Zubair Baloch, Virginia A. LiVolsi, Syl L., Juan Rosaí, Maria J. Merino, Gregory W. Randolph, Philippe Vielh, Richard M. DeMay, Mary Sidawy, William J. Frable

Bibliographic record

VenueDiagnostic Cytopathology · 2008
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineTerminologyThyroidFine-needle aspirationThyroid cancerBethesda systemPathologyCancerCytologyFine needle aspiration cytologyGeneral surgeryBiopsyInternal medicineLinguistics

Abstract

fetched live from OpenAlex

The National Cancer Institute (NCI) sponsored the NCI Thyroid Fine-needle Aspiration (FNA) State of the Science Conference on October 22-23, 2007 in Bethesda, MD. The two-day meeting was accompanied by a permanent informational website and several on-line discussion periods between May 1 and December 15, 2007 (http://thyroidfna.cancer.gov). This document summarizes matters regarding diagnostic terminology/classification scheme for thyroid FNA interpretation and cytomorphologic criteria for the diagnosis of various benign and malignant thyroid lesions. (http://thyroidfna.cancer.gov/pages/info/agenda/).

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)0.012
metaresearch head score (Gemma)0.014
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: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.007
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0020.003

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 head0.070
GPT teacher head0.326
Teacher spread0.256 · 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
GenreMethods

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

Citations885
Published2008
Admission routes1
Has abstractyes

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