Bibliographic record
Abstract
Abstract Purpose In an attempt to understand some of the reasons why some optic nerves appear to be sensitive to IOP and others not, I will review studies describing the interaction between vascular and biomechanical factors in open angle glaucoma. Methods Studies using biomechanical modelling, epidemiologic data, measurements of ocular or systemic blood flow, measurment of peripheral vasospasticity, and measurement of ocular biomechanical parameters will be reviewed. Hypotheses will be presented regarding the interpretation of these data. Results Studies suggest that the optic nerves of vasospasctic patients may be more IOP‐sensitive than those of non‐vasospastic patients. Non‐invasive measurements of ocular blood flow suggest that this pressure‐sensitivity may be related to IOP‐sensitive optic nerve blood flow. Biomechanical modelling suggests that scleral and lamina cribrosa elasticity, axial length, and eye wall thickness contribute to optic nerve head stress and strain. Cross‐sectional clinical data supports the role of increased ocular elasticity in the susceptibilty of the optic nerve to glaucoma damage, especially in vasospastic patients. Some promising new avenues for research in this area will be presented. Conclusion There is increasing evidence that biomechanical and vascular ocular factors interact leading to an elevated susceptibilty of the optic nerve to glaucomatous optic nerve damage. Commercial interest
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".