Optimal Targeting Display for Navigated Pelvic Screw Insertions
Bibliographic record
Abstract
Surgical navigation can be used for complex orthopaedic procedures, such as iliosacral screw fix- ations, to achieve accurate and efficient results [11]. Although there have been studies studying the impact of navigation systems on surgical outcomes [6, 3], we are not aware of any studies that have quantified the effect of how information regarding the surgical navigation scene is displayed to surgeons on conventional monitors. However, the display of information can have a measurable effect on both accuracy and time required to perform the navigated surgery, as the surgical scene can be presented in many different formats [9]. Optimizing surgical accuracy potentially helps improves patient safety by reducing screw malplacement [11], while optimiz- ing time efficiency reduces opportunity cost [1]. Therefore, we designed a study to determine the optimal visualizations for performing navigated pelvic screw insertions. The findings of this study can be used to more systematically design visualization components of a navigation system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".