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Record W1997282226 · doi:10.2310/7750.2014.14094

Dermatologic Surgical Pearls: Tips for Closing a Defect under Tension

2015· review· fr· W1997282226 on OpenAlexaff
Mélissa Nantel-Battista, Christian Murray

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2015
Typereview
Languagefr
FieldMedicine
TopicDigital Imaging in Medicine
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineDermatologic surgeryClosing (real estate)Closure (psychology)Psychological interventionSurgeryNursingLaw

Abstract

fetched live from OpenAlex

Dermatologic surgery procedures can sometimes be time consuming in an office setting. We present a series of tips for dermatologists and dermatologic surgeons that will enhance the efficiency of simple procedures. This article reviews three methods to aid in the closure of defects under tension. Les interventions en chirurgie dermatologique peuvent parfois prendre beaucoup de temps en cabinet. Nous présentons une serie de conseils à l'intention des dermatologues et des chirurgiens dermatologues, qui accroîtront l'efficacité de petites interventions. Seront expliquées dans l'article trois techniques visant â faciliter la fermeture des pertes de substance sous tension.

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)0.006
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.577
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.133
GPT teacher head0.380
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2015
Admission routes1
Has abstractyes

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