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Record W2051050273 · doi:10.1055/s-2007-967747

Minimally Invasive Levator Advancement: A Practical Approach to Eyelid Ptosis Repair

2007· article· en· W2051050273 on OpenAlexaff
Hector McDonald

Bibliographic record

VenueSeminars in Plastic Surgery · 2007
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineEyelidPtosisSurgeryForm and function

Abstract

fetched live from OpenAlex

There are many established plastic surgical techniques to effectively address blepharoptosis. Minimally invasive levator advancement (MILA) causes limited disruption to the anatomy while maintaining good height, contour, lid folds, function, and long-term stability. This procedure has been performed in more than 1000 patients since 1993 by the author with consistent, durable results and is a reliable method to correct blepharoptosis. It is not indicated in cases with absent to very poor levator function, where frontalis suspension is the preferred procedure. The MILA technique will be described and illustrated. KEYWORDS Minimally invasive levator advancement (MILA) - classic levator advancement (CLA) - avascular pyramid - attenuated levator aponeurosis - orbicularis shift

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.003

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 head0.033
GPT teacher head0.320
Teacher spread0.287 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations8
Published2007
Admission routes1
Has abstractyes

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Same venueSeminars in Plastic SurgerySame topicFacial Rejuvenation and Surgery TechniquesFrench-language works237,207