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Record W2141566703 · doi:10.1001/archfaci.9.1.9

Midface Effects of the Deep-Plane vs the Superficial Musculoaponeurotic System Plication Face-lift

2007· article· en· W2141566703 on OpenAlexaff
Peter A. Adamson, Ravi Dahiya, Jason A. Litner

Bibliographic record

VenueArchives of Facial Plastic Surgery · 2007
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineLift (data mining)OrthodonticsSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine if there is any observable difference in the midface of patients who have undergone a deep-plane face-lift vs a standard superficial musculoaponeurotic system (SMAS) plication face-lift. DESIGN: Preoperative and postoperative photographs of 25 patients undergoing each type of face-lift were rated by 3 independent and blinded observers. A 7-point scale was used to grade improvement in 5 areas on the face and neck: malar eminence, melolabial fold, jowls, cervicomental angle, and anterior neck banding. RESULTS: All 3 independent observers rated the patients who underwent a deep-plane face-lift as having a significantly better result (P<.01) in 2 of the measured locations; the observed improvements in the deep-plane group were twice those in the SMAS plication group. CONCLUSION: In our study of 50 patients, the deep-plane face-lift proved to have results that were clinically and statistically better than those of the SMASapplication face-lift in both the midface and the neck.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.237
Teacher spread0.226 · 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 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

Citations50
Published2007
Admission routes1
Has abstractyes

Explore more

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