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Record W2807663611 · doi:10.1177/2513826x17754056

MEDPOR Nipple Implant Causing Failure of Previously Stable Breast Implant

2018· article· en· W2807663611 on OpenAlexaffvenue
Zach Zhang, Murray Allen, Kirsty U Boyd

Bibliographic record

VenuePlastic Surgery Case Studies · 2018
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBreast reconstructionImplantMedicineSurgeryComplicationDentistryBreast cancerInternal medicineCancer

Abstract

fetched live from OpenAlex

Reconstruction of the nipple–areolar complex usually marks the final stage of breast reconstruction in postmastectomy patients. There are many approaches to the nipple reconstruction using autologous, allogenic, and synthetic materials. However, different methods have their own pros and cons and there is no current consensus for the best technique. A review of the literature showed that there is a low level of evidence for synthetic material–based nipple reconstruction providing the best nipple projection, but it is also associated with more complication. We present a case where revision of nipple reconstruction with MEDPOR implant overlying an implant-based breast reconstruction preceded the loss of both the nipple and breast construction secondary to infection.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.279
Teacher spread0.246 · 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
Published2018
Admission routes2
Has abstractyes

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