Interface vitréomaculaire : Série de cas d’adhérence et de traction
Bibliographic record
Abstract
L’interface vitréomaculaire a toujours été difficile à évaluer sur le plan clinique. Cependant, avec l’avènement de la tomographie par cohérence optique, les pathologies à cette interface sont plus faciles à diagnostiquer et à surveiller. Les attaches de l’interface vitréomaculaire sont diverses, allant de l’adhérence sans changement de la structure fovéale, comme l’adhérence vitréomaculaire, aux tractions entraînant un changement de structure, comme la traction vitréomaculaire. Bon nombre de ces pathologies peuvent être observées et prises en charge par un optométriste sans consulter un spécialiste de la rétine. Cet article décrit trois cas de pathologie vitréomaculaire accompagnés d’un examen du système de classement, de présentations qui ont été associées à une incidence plus élevée de libération spontanée et d’options de traitement.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".