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Record W2087418752 · doi:10.1001/jamafacial.2014.789

The Aesthetic Unit Principle of Facial Aging

2014· article· en· W2087418752 on OpenAlexaff
Susan Tan, Michael G. Brandt, Jeffrey C. Yeung, Philip C. Doyle, Corey C. Moore

Bibliographic record

VenueJAMA Facial Plastic Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsSt Joseph's Health CareUniversity of OttawaLondon Health Sciences CentreUniversity of TorontoWestern University
Fundersnot available
KeywordsStimulus (psychology)PsychologyMedicineAestheticsCognitive psychologyArt

Abstract

fetched live from OpenAlex

IMPORTANCE: In youth, facial aesthetic units flow together without perceptible division. The face appears as a single dynamic structure with a smooth contour and very little if any shadowing between different anatomical regions. As one ages, facial aesthetic units slowly become distinct. This process may be a consequence of differences in skin thickness, composition of subcutaneous tissue, contour of the facial skeleton, and location of facial ligaments. Although the impact of aesthetic unit separation is clinically apparent, its fundamental role in perceived facial aging has not yet been defined empirically. OBJECTIVES: To evaluate and define the effect of aesthetic unit separation on facial aging and to empirically validate the rationale for the blending of aesthetic units as a principle for facial rejuvenation. DESIGN, SETTING, AND PARTICIPANTS: We prepared the photographs of 7 women for experimental evaluation of the presence or absence of facial aesthetic unit separation. Photographic stimuli were then presented to 24 naive observers in a blinded paired comparison. For each stimulus pair, observers were asked to select the facial photograph that they considered to be more youthful in appearance. Each stimulus was compared with all others. MAIN OUTCOMES AND MEASURES: We calculated a preference score for the total number of times any photograph was chosen to be more youthful compared with all others. Paired t tests were used to compare the preference scores between the facial stimuli with and without aesthetic unit separation. RESULTS: We generated 4032 responses for analysis. Photographs without facial aesthetic unit separation were consistently judged to be more youthful than their aged original or modified counterparts, with mean preference scores of 0.66 and 0.33, respectively (P ≤ .047). When we selected the paired stimulus that directly compared one photograph with aesthetic unit separation with another with blended aesthetic units (2015 pairs), observers indicated that the photograph with the blended aesthetic unit was younger 95% of the time. Within-rater reliability was found to be very good (r = 0.88). CONCLUSIONS AND RELEVANCE: Our data support the hypothesis that facial aesthetic unit separation influences perceived facial youthfulness among photographs of women. The presence of facial aesthetic unit separation results in a less youthful appearance. Based on these empirical data, the concept of facial aesthetic unit separation appears to play a significant role in perceived facial aging. LEVEL OF EVIDENCE: NA.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.283
Teacher spread0.258 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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