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Record W2567689439 · doi:10.3390/cancers9010001

Retroareolar Carcinomas in Breast Ultrasound: Pearls and Pitfalls

2016· review· en· W2567689439 on OpenAlexaff
Romuald Ferré, Martine Paré, Lisa A. Smith, Mélanie Thériault, Ann Aldis, Ellen Kao, Benoı̂t Mesurolle

Bibliographic record

VenueCancers · 2016
Typereview
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsMcGill UniversityRoyal Victoria Regional Health CentreRoyal Victoria HospitalThunder Bay Regional Health Sciences Centre
Fundersnot available
KeywordsMedicineMedical physicsRadiology

Abstract

fetched live from OpenAlex

Breast Ultrasound (US) is an important tool for both screening and diagnostic examinations. Although breast US has benefitted from significant recent technical improvements, its use for the retroareolar region is known to be more challenging than for other locations. The retroareolar location was defined by Giess et al. in 1998 as the region where any lesion is situated at less than two cm from the nipple and/or involves the nipple-areolar complex on mammogram. Understanding of the complex anatomy and physiology of the nipple-areolar region is important to avoid misinterpretation and misdiagnosis. The ability for the breast imager to manage difficulties related to the retroareolar area is paramount by adjusting settings (compounding, frequency, Doppler) and utilizing specific manoeuvers. Cases illustrating difficulties encountered in diagnosis of retroareolar carcinomas are presented.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.295
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 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

Citations75
Published2016
Admission routes1
Has abstractyes

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