Bibliographic record
Abstract
The purpose of this manuscript is to review the design, development and clinical results of the light adjustable lens (LAL). Evolution in techniques, biometry and intraocular lens (IOL) calculation have improved outcomes and increased expectations after cataract surgery. Nevertheless, Imprecise IOL power determinations, pre-existing and surgical-induced astigmatism, and previous corneal refractive surgery continue to limit post-operative uncorrected vision. The LAL was designed to provide a stable, precise correction of refractive errors with a safe, non-invasive post-operative procedure. The concept behind the LAL is based on photochemistry and diffusion. The adjustment occurs when all non-attached solutes equally distribute themselves throughout the optic after irradiation with ultraviolet light that causes the photosensitive macromers to polymerise in the irradiated region. Clinical results have been positive, with the largest series (122 eyes) showing 97 % of patients within 0.25 D of attempted spherical equivalent and 100 % uncorrected vision 20/25 or better. In conclusion, the LAL has demonstrated to be a safe, accurate and reliable method of post-operative, non-surgical correction of residual sphero-cylindrical refractive error.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".