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Record W2122605777 · doi:10.1002/jcu.22070

Imaging of fat‐containing lesions of the breast: A pictorial essay

2013· review· en· W2122605777 on OpenAlex
Anoop Ayyappan, Pavel Crystal, Alireza Torabi, Bryan Foley, Bruno D. Fornage

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

VenueJournal of Clinical Ultrasound · 2013
Typereview
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsWomen's College HospitalUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsMedicineUltrasonographyRadiologyBreast imagingMammographyMagnetic resonance imagingFat necrosisImaging techniqueUltrasoundPathologyBreast cancerCancerInternal medicine

Abstract

fetched live from OpenAlex

Fat-containing breast lesions constitute a heterogeneous group of predominantly benign tumors and non-neoplastic conditions. The role of imaging is to distinguish leave-me-alone lesions from rarely occurring malignant fat-containing tumors that require histologic analysis. Correlating mammographic findings with appearance at ultrasonography often helps in identifying lesions that do not require further work-up. MRI can be valuable to confirm the presence of fat and characterize lesions indeterminate on conventional imaging. The purpose of this multimodality imaging review is to exemplify the radiologic appearances of common and uncommon fat-containing breast lesions to facilitate accurate diagnosis, avoid unnecessary interventions, and ensure appropriate management.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.978
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.098
GPT teacher head0.418
Teacher spread0.320 · 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