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Record W2802872784 · doi:10.3390/diagnostics8020028

Fine Needle Aspiration Cytology for Neck Masses in Childhood. An Illustrative Approach

2018· review· en· W2802872784 on OpenAlexafffund
Consolato Sergi, Aneesh Dhiman, Jo-Ann Gray

Bibliographic record

VenueDiagnostics · 2018
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsUniversity of Alberta
FundersUniversity of AlbertaWomen and Children's Health Research InstituteChildren's Health Research Institute
KeywordsMedicineThyroidNodule (geology)Differential diagnosisNeck massRhabdomyosarcomaCytologyFine-needle aspirationMalignancyRadiologyFine needle aspiration cytologyThyroid carcinomaHead and neckOtorhinolaryngologyCarcinomaPathologySurgeryBiopsySarcomaInternal medicine

Abstract

fetched live from OpenAlex

The primary indication of fine-needle aspiration cytology of the head and neck region is a thyroid nodule or a mass located in the cervical area or the head. Although a thyroid nodule may raise the suspicion of malignancy, less than one in 20 cases results in a carcinoma. In addition, the list of differential diagnoses is quite different according to the age of the patient. A number of benign lesions, such as branchial cysts, sialadenosis, and sialoadenitis are often seen in childhood and youth. The malignant lesions that are on the top of the list of a pediatric mass of the head and neck (H&N) region include rhabdomyosarcoma, neuroblastoma, and papillary carcinoma of the thyroid gland. This critical review of the diagnostic features of a pediatric mass of the H&N region is accompanied by panels of several cytology features that may be of help to the cytopathologist and clinician.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.109
GPT teacher head0.389
Teacher spread0.280 · 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
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

Citations20
Published2018
Admission routes2
Has abstractyes

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