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A Validated Grading Scale for Marionette Lines

2008· article· en· W2133894223 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDermatologic Surgery · 2008
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntraclass correlationRating scaleGrading (engineering)Scale (ratio)Artificial intelligenceComputer scienceOrthodonticsPsychologyMathematicsMedicineStatisticsPsychometricsCartographyGeographyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Melomental folds, or marionette lines, are one of the consequences of facial aging. The curvilinear wrinkles formed because of facial movements and the aging process extend downward from the oral commissures. OBJECTIVES: To develop the Marionette Lines Grading Scale for objective quantification of the severity of melomental folds and to establish the reliability of this photonumeric scale for clinical research and practice. MATERIALS AND METHODS: A 5-point photonumeric rating scale was developed to objectively quantify the severity of melomental folds. Nine experts rated photographs of 35 subjects, twice, with regard to marionette lines in comparison with morphed images. Inter- and intrarater variability was assessed by computing intraclass correlation coefficients. RESULTS: The agreement between the experts was high. Bubble plots (bivariate scatter plots) demonstrated linearity in judgment by the experts. CONCLUSION: The 5-point photonumeric scale generated spans the severity of marionette lines for which patients commonly seek correction. The scale is well stratified for consistent rating.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.088
GPT teacher head0.302
Teacher spread0.214 · 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