On Enhancing Planning and Navigation of Beating-Heart Mitral Valve Surgery Using Pre-operative Cardiac Models
Why this work is in the frame
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Bibliographic record
Abstract
In an effort to reduce morbidity during minimally-invasive cardiac procedures, we have recently developed an interventional technique targeted towards off-pump cardiac interventions. To compensate for the absence of direct visualization, our system employs a virtual reality environment for image guidance, that integrates pre-operative information with real-time intra-operative imaging and surgical tool tracking. This work focuses on enhancing intracardiac visualization and navigation by overlaying pre-operative cardiac models onto the intra-operative virtual space, to display surgical targets within their specific anatomical context. Our method for integrating pre-operative data into the intra-operative environment is accurate within 5.0 mm. Thus, we feel that our virtually-augmented surgical space is accurate enough to improve spatial orientation and intracardiac navigation.
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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 | 0.001 |
| 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