The evolution of virtual reality in shoulder and elbow surgery
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
Virtual Reality (VR) in orthopedic surgery has significantly increased in popularity in the areas of preoperative planning, intraoperative usage, and for education and training; however, its utilization lags behind other surgical disciplines and industries. The use of VR in orthopedics is largely focused on education and is currently endorsed by North American and European training committees. The use of VR in shoulder and elbow surgery has varying levels of evidence, from I to IV, and typically involves educational randomized controlled trials. To date, however, the terms and definitions surrounding VR technology used in the literature are often redundant, confusing, or outdated. The purpose of this review, therefore, was to characterize previous uses of VR in shoulder and elbow surgery in preoperative, intraoperative, and educational domains including trauma and elective surgery. Secondary objectives were to provide recommendations for updated terminology of immersive VR (iVR) as well as provide a framework for standardized reporting of research surrounding iVR in shoulder and elbow surgery.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it