Bibliographic record
Abstract
The transplant of a complete eyeball, with its blood supply and the critical optic nerve that connects it to the brain, has been seen as an impossible objective in the fight against blindness.1On May 28, 2023, surgeons at NYU Langone Health made history by performing the world's first complete human eye transplant.1 The patient, Aaron James, was a 46-year-old veteran from Arkansas who had lost most of his face and one eye in an accident involving high-voltage power lines.1 Upon learning of James' situation, face transplant specialists at NYU Langone Health proposed not just a partial face transplant but also a whole-eye transplant, a procedure that had never been performed before.2 More than 140 surgeons, nurses, and healthcare workers arrived at NYU Langone on the day of James' procedure and were divided into two teams, one removing the sections of James' face that would be replaced with donor tissue and the other removing the donor's face and eyeball.2 The ground-breaking procedure lasted 21 hours.2 Though James may not be able to see out of the transplanted eye, he is recovering well after the dual transplant.2 The donated eye appears to be in good health, revealing unparalleled insights into how the human eye can heal.1
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.009 |
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".