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Nipple reduction - An adjunct to augmentation mammaplasty

2009· article· en· W4232090185 on OpenAlexaff
Nabil Fanous, Carolyne Tawilé, Amanda Fanous

Bibliographic record

VenuePlastic Surgery · 2009
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsMcGill UniversityLakeshore General HospitalInstitute of Cosmetic and Laser Surgery
Fundersnot available
KeywordsAdjunctMammaplastyReduction (mathematics)MedicineSurgeryMathematicsPhilosophy

Abstract

fetched live from OpenAlex

N ipple hypertrophy and its reduction have been described in a limited number of articles throughout the medical literature (1-8). Nipple hypertrophy is an uncommon esthetic problem. The epidemiology of this deformity remains largely unknown; it is mostly encountered in the Asian population and, occasionally, in Caucasians. It is sometimes familial, appearing after the onset of adolescence or following pregnancy, and persisting through menopause (1). It may lead to psychological distress because of its association with a negative esthetic image. As well, women may feel embarrassed by their hypertrophic nipples, which are hard to conceal under light clothing because of their prominence.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.027
GPT teacher head0.268
Teacher spread0.241 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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