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 present a new technique, macular hole hydrodissection, that increases the likelihood of closure for challenging macular holes (MHs) with multiple risk factors. METHODS: A retrospective review of all consecutive eyes with idiopathic Stage 3 and 4 MHs that were either persistent (failed previous vitrectomy surgery), chronic (symptoms of central vision loss of ≥2 years or a clinical diagnosis for ≥1 year), and/or large (aperture diameter of ≥400 μm), having undergone the macular hole hydrodissection surgical technique between January 1, 2014, and May 1, 2017, from an institutional practice setting was conducted. This technique lyses retina-retinal pigment epithelium adhesions by injecting fluid into the MH and allows for successful closure as the mobile edges are then brought closer together. RESULTS: Thirty-nine eyes of 39 patients with mean MH aperture and base diameters of 549.1 ± 159.47 μm and 941.97 ± 344.14 were included. Complete anatomical closure was achieved in 87.2% (34/39) of MHs. Vision improvement was observed in 94.9% (37/39) and gain of ≥2 lines was achieved in 79.5% (31/39). Of the MHs that achieved anatomical success, 100% (34/34) had a Type 1 closure. The mean postoperative follow-up was 320.33 ± 269.04 days. CONCLUSION: The macular hole hydrodissection surgical technique improves anatomical and functional outcomes of persistent, chronic, and/or large MHs.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it