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Twelve-year delay of a nipple-sharing graft: A case report.

2013· article· en· W4239937465 on OpenAlexaff
Tatiana KS Cypel, M. Catherine Brown

Bibliographic record

VenuePlastic Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicOrgan and Tissue Transplantation Research
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsMedicineSurgery

Abstract

fetched live from OpenAlex

S urgical treatment of breast cancer has evolved from radical mastec- tomy with removal of the nipple areolar complex (NAC), to breast conservation therapy with preservation of the breast and NAC. Increasing interest in improved cosmesis has led to the introduction of the skin-sparing and nipple-sparing mastectomy as potential alternatives to complete mastectomy (1). There continue to be clinical situations in which the NAC is removed to either treat disease or as a component of breast cancer risk reduction. Several techniques are available to reconstruct the NAC. Achievement of consistent quality results remains a challenge. Often, multiple surgical procedures are required to achieve an acceptable cosmetic outcome. Jabor et al (2) reported a high level of dissatisfaction with NAC reconstructions, with only 16% of patients stating they had no desire to change their reconstruction. The remaining patients reported, in decreasing order, dissatisfaction with the nipple projection, colour match, shape, size, texture and position of their reconstructed NAC. Holding to the principle of reconstructing like tissue with like tissue, the nipple-sharing composite graft is an ideal approach for unilateral reconstruction. Requirements for this technique include unilateral reconstruction, a donor nipple of adequate size and patient consent for partial removal of the remaining normal nipple.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0040.000

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 head0.042
GPT teacher head0.297
Teacher spread0.255 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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