Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To investigate if specific classes of antiglaucoma medications have an influence on selective laser trabeculoplasty (SLT) success. METHODS: This retrospective prediction rule analysis investigated 120 eyes from 120 patients diagnosed with either open angle glaucoma or ocular hypertension, who underwent SLT treatment. Treatment success was defined as ≥20% intraocular pressure (IOP) reduction at 3 and 6 months after the treatment date. Multivariate logistic regression analyses were performed to determine success predictors. RESULTS: Pre-SLT IOP (up to 4 wk before SLT therapy) was the only independent predictor for ≥20% IOP reduction with an odds ratio of 1.30 when controlling for pre-SLT antiglaucoma drops. The area under receiver operator characteristic curve was 0.777. CONCLUSIONS: Topical medications do not adversely, nor favorably, affect SLT success. SLT efficacy is positively associated with the degree of IOP elevation before SLT treatment. Pigmentation of the anterior chamber angle, class of antiglaucoma medications, diabetes, sex, corneal thickness, pseudophakia, diagnosis, washout of eye drops, and previous argon laser trabeculoplasty treatment are not associated with SLT treatment efficacy.
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.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it