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Record W2932472070

Bilateral Peri-Orbital Skin Lesions

2014· article· en· W2932472070 on OpenAlexaboutno aff
Hussein Abujrad MBBCh, Heather Lochnan

Bibliographic record

VenueInternational Journal of Clinical & Medical Images · 2014
Typearticle
Languageen
FieldMedicine
TopicCancer and Skin Lesions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineApocrineEyelidSWEATEccrine sweat glandSurgerySweat glandDermatologyAnatomyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

A 67 year-old male presented with bilateral painless periorbital lesions that appeared to be cystic. These lestions became apparent one year prior and were progressing in size. He described having similar lesions removed many years previously, but they were not as dramatic at that time (Figure 1). His medical history was significant for hypogonadism and hyperprolactinemia recently diagnosed and found to be secondary to a pituitary microadenoma (Microprolactinoma) and he is known to have significant coronary artery disease. His family history was unremarkable. The patient was referred to the dermatological assessment and Hidrocystoma (Eccrine) was diagnosed and treated with surgical drainage. Hidrocystomas are benign, cystic, sweat gland tumours of the skin that occur mostly in adults between 30 and 70 years of age. They are classified as either apocrine or eccrine. Apocrine hidrocystomas arise from the proliferation of apocrine glands and are usually solitary, with a diameter of 3–15 mm. Eccrine hidrocystomas result from cystic dilation due to retention of sweat and blockage of the sweat duct. They are tense, dome-shaped cysts, ranging from 1 to 6 mm in diameter and usually affect the periorbital and malar areas but do not involve the eyelid margin. They may have an amber, brown, or bluish tint. Our patient has no recurrence of the hidrocystomas after 10 months of the surgical drainage and no obvious connection to his prolactinoma can be made. Corresponding authors Hussein Abujrad and Heather Lochnan Division of Endocrinology and Metabolism University of Ottawa Canada

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)0.001
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.043
GPT teacher head0.465
Teacher spread0.422 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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