Post-operative imaging in deep brain stimulation: A controversial issue
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Bibliographic record
Abstract
In deep brain stimulation (DBS), post-operative imaging has been used on the one hand to assess complications, such as haemorrhage; and on the other hand, to detect misplaced contacts. The post-operative determination of the accurate location of the final electrode plays a critical role in evaluating the precise area of effective stimulation and for predicting the potential clinical outcome; however, safety remains a priority in postoperative DBS imaging. A plethora of diverse post-operative imaging methods have been applied at different centres. There is neither a consensus on the most efficient post-operative imaging methodology, nor is there any standardisation for the automatic or manual analysis of the images within the different imaging modalities. In this article, we give an overview of currently applied post-operative imaging modalities and discuss the current challenges in post-operative imaging in DBS.
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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 | 0.001 |
| 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 | 0.001 |
| 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