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Record W2409986514 · doi:10.1097/rlu.0000000000000924

Cholesterol Granuloma

2015· article· en· W2409986514 on OpenAlexaff
Patrick Martineau, Matthieu Pelletier‐Galarneau, Eugene Leung

Bibliographic record

VenueClinical Nuclear Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicEar and Head Tumors
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineNodule (geology)MalignancyLesionMammographyGranulomaBiopsyRadiologyMelanomaPathologyPyogenic granulomaSoft tissueBreast cancerInternal medicineCancer

Abstract

fetched live from OpenAlex

Cholesterol granulomas are benign lesions, rarely seen in the breast, which are indistinguishable from malignancy on anatomical imaging. The FDG PET/CT of a patient referred for melanoma staging revealed a mildly FDG-avid, soft tissue nodule in the left breast. This finding was felt unlikely to represent metastatic melanoma due to the relatively low level of uptake. The lesion was not seen on follow-up mammography. Ultrasound-guided biopsy was performed, which identified this lesion as a cholesterol granuloma. This case illustrate that cholesterol granuloma can be misinterpreted as a malignant lesion on both anatomical imaging and FDG PET/CT.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.255
GPT teacher head0.462
Teacher spread0.206 · 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 designCase report
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

Citations15
Published2015
Admission routes1
Has abstractyes

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