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Record W6950591069 · doi:10.5281/zenodo.7674063

How to Preserve Complete Breastfeeding Function in Breast Reduction and Lifting Mammaplasties

2023· article· en· W6950591069 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBreastfeedingBreast reductionReduction (mathematics)Breast tissueBreast feedingMammaplastyBreast cancer

Abstract

fetched live from OpenAlex

Breastfeeding has been shown to provide considerable benefits to newborn and maternal health. The World Health Organization recommends exclusive breastfeeding of babies up to six months of age. It is well known that breast reduction techniques that preserve the column of subareolar breast tissue have a greater likelihood of successful postoperative breastfeeding. The best representative of these techniques is the Total Posterior Pedicle breast reduction which was described by Richard Moufarrege since 1982. It consists of dissecting the skin away from the breast tissue offering free access to all breast quadrants. This technique is known for its robust blood supply to the nipple areolar complex, the preservation of the nipple areolar complex sensation, and for its low rate of long-term complications such as pseudoptosis. In this article, we demonstrate that the Moufarrege Total Posterior Pedicle preserves breastfeeding function in women undergoing breast reduction using this technique.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.237
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicBreast Implant and ReconstructionFrench-language works237,207