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Record W2023720877 · doi:10.1007/s00268-011-1319-9

Accuracy of Axillary Ultrasound in the Diagnosis of Nodal Metastasis in Invasive Breast Cancer: A Review

2011· review· en· W2023720877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWorld Journal of Surgery · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineBreast cancerRadiologySentinel nodeBiopsySentinel lymph nodeAxillary Lymph Node DissectionUltrasoundLymph nodeFine-needle aspirationDissection (medical)Stage (stratigraphy)CancerSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Axillary lymph node status is the most important prognostic factor in early-stage breast cancer. Sentinel lymph node biopsy is used to determine the need for axillary node dissection. This technique incurs cost associated with radio-isotope administration and use of the operating room. Accordingly, there is a need to preoperatively identify patients with nodal metastases who can proceed directly to axillary dissection. Axillary ultrasound has increasingly been used to determine nodal status prior to surgery. It has been shown to be a sensitive and specific modality in the detection of nodal metastases. When combined with fine-needle aspiration, the specificity of this modality significantly increases. Here we present a current review of the usefulness of preoperative axillary ultrasound in early and locally advanced breast cancer patients with and without fine-needle aspiration biopsy. Based on this review, we estimate the proportion of patients that can be spared a sentinel lymph node biopsy and the concomitant benefit of axillary ultrasound in terms of cost.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.918
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.075
GPT teacher head0.339
Teacher spread0.264 · 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