Developing an Analytical NMR Technique for Studying Interactions between Spin-Coated Contact Lens Materials and Soluble Proteins
Bibliographic record
Abstract
Contact lenses are versatile and non-invasive therapeutic devices used to treat a wide range of ocular disorders, including impaired vision, and can also act as a platform to deliver drugs directly to the eyes. Despite their utility, discomfort caused by long-term contact lens use is a significant cause of contact lens discontinuation, which can negatively affect quality-of-life and health of users. While it is known that a host of tear film proteins adsorb onto polymeric contact lens materials, the impact of lens material formulations and chemical structures on ocular proteins adsorption, and ultimately on wearer discomfort, is still not clear. Many current tools for studying protein-surface interactions lack the ability to provide insight into how contact lens materials interact with proteins on a molecular level. My thesis aims to address this problem by developing an analytical NMR technique for characterizing molecular-level interactions between contact lens materials and soluble proteins.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".