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Record W3163864955 · doi:10.1111/jocd.14225

Hair transplantation Follicular Unit Excision (FUE): Introducing the multipurpose octagonal ring punch

2021· article· en· W3163864955 on OpenAlexaff
Roberto Trivellini, Aditya K. Gupta

Bibliographic record

VenueJournal of Cosmetic Dermatology · 2021
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsHair transplantationDermisTransplantationHair follicleSurgeryMedicineComputer scienceAnatomy

Abstract

fetched live from OpenAlex

The technique of follicular unit excision for harvesting grafts for hair transplantation procedures has become very popular. This technique relies on the use of small punches to remove viable grafts. Many different punch shapes have been developed to accommodate the varying nature of skin and hair characteristics, resulting in hair transplant surgeons requiring a variety of punches to suit a wide range of patients, which can be overwhelming to the beginner when trying to decide on the optimal choice of a punch to suit a particular skin characteristic. We describe a novel multipurpose ring punch that can be used on patients with a variety of skin and hair characteristics, as well as for shaved and long hair FUE. Features of this punch include an octagonal ring that protrudes from the outer wall of the punch and functions to control the punch's trajectory into the deeper dermis during incision. Additionally, this punch has a dull, notched edge which allows for use in long hair and shaved FUE without sacrificing ease of incision through the epidermis. This punch is the first of its kind to have this breadth of versatility with a one-size-fits-all design.

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 score0.357
Threshold uncertainty score0.376

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 head0.014
GPT teacher head0.276
Teacher spread0.262 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

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