The role of stereopsis in microsurgical performance on the EYESi ophthalmic surgical simulator
Bibliographic record
Abstract
<i>Introduction</i>: There remains a lack of compelling objective evidence on whether stereopsis is necessary for an ophthalmic surgical career. It is also unclear if high-grade stereoacuity correlates with better surgical performance. The present study attempts to address this question by comparing the simulated surgical performance of subjects with different levels of stereoacuity using a virtual reality (VR) intraocular surgical simulator (EYESi, VRmagic, Mannheim, Germany). <i>Methods</i>: Subjects were tested based on their stereoacuity level and stratified in three age-matched groups: normal stereopsis, subnormal stereopsis, and patients with no measurable stereoacuity in the clinical setting. Eleven subjects in each group to make a total of 33 subjects with no prior surgical experience were recruited from the IWK Health Centre, Halifax, Canada (REB trial registration: 1023183). Subjects performed three attempts on a standardized microsurgical module on the EYESi VR simulator. <i>Results</i>: There was no significant main effect of the stereo-group that the participants belonged to on their total scores, or on the time needed to complete the task, or on the odometer value, or on the amount of injury to surrounding tissues. <i>Discussion</i>: This study showed that for a basic simulated microsurgical task on the EYESI intraocular surgical simulator, the performance of individuals with reduced and absent stereoacuity was statistically indistinguishable from those with normal stereoacuity. Therefore, caution is still recommended when advocating for mandatory high level of stereoacuity as a requirement for admission to training programs in ophthalmology. There is still definite need for solid evidence that stereopsis is necessary to achieve satisfactory skills in ophthalmic microsurgery.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.078 | 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".