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Record W3178733117 · doi:10.1055/s-0041-1731793

Current Concepts in Capsular Contracture: Pathophysiology, Prevention, and Management

2021· review· en· W3178733117 on OpenAlex
Tyler Safran, Hillary Nepon, Carrie K. Chu, Sebastian Winocour, Amanda Murphy, Peter Davison, Tassos Dionisopolos, Joshua Vorstenbosch

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSeminars in Plastic Surgery · 2021
Typereview
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsMcGill University
Fundersnot available
KeywordsCapsular contractureMedicineBreast augmentationContractureEtiologyIntensive care medicinePathophysiologyComplicationImplantSurgeryPathologyInternal medicineBreast reconstructionBreast cancer

Abstract

fetched live from OpenAlex

Over 400,000 women in the United States alone will have breast implant surgery each year. Although capsular contracture represents the most common complication of breast implant surgery, surgeons continue to debate the precise etiology. General agreement exists concerning the inflammatory origin of capsular fibrosis, but the inciting events triggering the inflammatory cascade appear to be multifactorial, making it difficult to predict why one patient may develop capsular contracture while another will not. Accordingly, researchers have explored many different surgical, biomaterial, and medical therapies to address these multiple factors in an attempt to prevent and treat capsular contracture. In the current paper, we aim to inform the reader on the most up-to-date understanding of the pathophysiology, prevention, and treatment of capsular contracture.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.332
Teacher spread0.304 · 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