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'Optimum mobility' facelift. Part 1 – the theory

2006· article· en· W4246185707 on OpenAlexaff
Nabil Fanous

Bibliographic record

VenuePlastic Surgery · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceMathematical economicsMathematics

Abstract

fetched live from OpenAlex

Traditional rhytidectomy techniques, such as the cutaneous lift, the superficial musculoaponeurotic system lift, the deep plane lift and the subperiosteal lift, are mostly differentiated by their different planes of dissection. As well, many of these techniques consider the complete mobilization of tissues a prerequisite for obtaining a satisfactory result. However, is it true that the result of a rhytidectomy is linked to the choice of the dissection plane? Also, is it true that the adequacy of the surgical mobilization of tissues is vital to the outcome? The present paper discusses the above questions and introduces a factor that is believed to be crucial to the planning and success of a rhytidectomy: facial tissue mobility. The analysis of this mobility is presented and leads to the development of three theories: 'intrinsic mobility', 'surgically induced mobility' and 'optimum mobility points'. These theories form the foundation of a rhytidectomy technique termed 'optimum mobility' facelift.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.179
Teacher spread0.162 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2006
Admission routes1
Has abstractyes

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