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Record W2639454766 · doi:10.7759/cureus.1380

Radiotherapy in the Multidisciplinary Management of Adenomyoepithelioma of the Breast with an Axillary Lymph Node Metastasis: A Case Report and Review of the Literature

2017· article· en· W2639454766 on OpenAlexaff
Natalie Logie, Judith Hugh, Kim Paulson, R. Pearcey, Karen King

Bibliographic record

VenueCureus · 2017
Typearticle
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsInstitute of Cancer ResearchUniversity of Alberta
Fundersnot available
KeywordsMedicineRadiation therapyAxillary Lymph Node DissectionBiopsyLymph nodeAdjuvant radiotherapyMetastasisMastectomyAxillary lymph nodesLymphBreast cancerRadiologyDissection (medical)General surgerySurgerySentinel lymph nodeCancerPathologyInternal medicine

Abstract

fetched live from OpenAlex

We describe a case of aggressive adenomyoepithelioma (AME) of the breast with a lymph node metastasis. A 63-year-old female presented with a fluctuating breast mass and clinically palpable lymph nodes. The patient underwent excisional biopsy followed by mastectomy with lymph node dissection and adjuvant radiotherapy (RT). Clinical behavior of both benign and malignant AME is described with the review of the literature and treatment recommendations.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.296
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations14
Published2017
Admission routes1
Has abstractyes

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