Corneal Neurotization: Essentials for The Facial Paralysis Surgeon
Bibliographic record
Abstract
Deficits in corneal innervation lead to neurotrophic keratopathy (NK). NK is frequently associated with facial palsy, and corneal damage can be accelerated by facial palsy deficits. Corneal nerves are important regulators of limbal stem cells, which play a critical role in epithelial maintenance and healing. Nonsurgical treatments of NK have undergone recent innovation, and growth factors implicated in corneal epithelial renewal are a promising therapeutic avenue. However, surgical intervention with corneal neurotization (CN) remains the only definitive treatment of NK. CN involves the transfer of unaffected sensory donor nerve branches to the affected cornea, and a variety of donor nerves and approaches have been described. CN can be performed in a direct or indirect manner; employ the supraorbital, supratrochlear, infraorbital, or great auricular nerves; and utilize autograft, allograft, or nerve transfer alone. Unfortunately, comparative studies of these factors are limited due to the procedure's novelty and varied recovery timelines after CN. Regardless of the chosen approach, CN has been shown to be a safe and effective procedure to restore corneal sensation and improve visual acuity in patients with NK.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".