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A Validated Hand Grading Scale

2008· article· en· W4250398378 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
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGrading scaleIntraclass correlationGrading (engineering)Rating scaleMedicineBivariate analysisScale (ratio)OrthodonticsSurgeryStatisticsPsychometricsMathematicsClinical psychologyCartography

Abstract

fetched live from OpenAlex

BACKGROUND Following the popularity of facial cosmetic procedures to reverse the signs of aging, cosmetic procedures that rejuvenate the hand are being sought. Irregular surface pigmentation, prominence of superficial veins and tendons, thinning of the dermis, and loss of subcutaneous fat typically characterize aging of the hand. OBJECTIVES To develop the Hand Grading Scale for objective quantification of the severity of hand aging and to establish the reliability of this photonumeric scale for clinical research and practice. MATERIALS AND METHODS The Hand Grading Scale is a 5-point photonumeric rating scale that was developed to objectively quantify the severity of aging of the hand. Nine experts rated photographs of 35 subjects, twice, with regard to the aspect “hand aging” in comparison with morphed images. Inter- and intrarater variability was assessed by computing intraclass correlation coefficients. RESULTS The agreement between the experts was considerably high. Bubble plots (bivariate scatter plots) demonstrated linearity in judgment by the experts. CONCLUSION The 5-point photonumeric scale generated spans the severity of hand aging for which patients most 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.999

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)0.0010.001

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 head0.087
GPT teacher head0.294
Teacher spread0.207 · 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