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A Validated Grading Scale for Crow's Feet

2008· article· en· W2169353528 on OpenAlexaff
Alastair Carruthers, Jean Carruthers, Bhushan Hardas, Mandeep Kaur, ROMAN GOERTELMEYER, Derek Jones, Berthold Rzany, Joel L. Cohen, Martina Kerscher, Timothy C. Flynn, Corey S. Maas, Gerhard Sattler, Alexander Gebauer, Rainer Pooth, KATHLEEN MCCLURE, ULLI SIMONE-KORBEL, Larry Buchner

Bibliographic record

VenueDermatologic Surgery · 2008
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntraclass correlationGrading scaleRating scaleGrading (engineering)Intra-rater reliabilityInter-rater reliabilityMedicineCorrelationScale (ratio)Reliability (semiconductor)Physical therapyPhysical medicine and rehabilitationSurgeryStatisticsPsychometricsMathematicsCartographyClinical psychologyEngineeringGeography

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop the Crow's Feet Grading Scale for objective quantification of the severity of lateral canthal lines 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 lateral canthal lines at rest and at maximum contracture of the orbicularis oculi. Nine experts rated photographs of 35 subjects, twice, with regard to the aspect crow's feet in comparison with morphed images. Inter- and intrarater variability was assessed by computing intraclass correlation coefficients. RESULTS: The agreement between the experts was significantly high. Furthermore, the test-retest correlation coefficients were high for each expert after an overnight interval, demonstrating low inter- and intraevaluator variability. CONCLUSION: The 5-point photonumeric scale generated spans the severity of the type of crow's feet 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.

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)0.004
metaresearch head score (Gemma)0.011
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.098
GPT teacher head0.307
Teacher spread0.209 · 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

Citations86
Published2008
Admission routes1
Has abstractyes

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