Treatment Plan Robustness Under iPDT Source Position Uncertainty
Bibliographic record
Abstract
Significance Clinical iPDT operations cannot guarantee perfect dose delivery due to unavoidable uncertainties in both the power emitted precise position of a source. We use software tools to simulate and analyze the impact of uncertainties under angular variated insertions. Approach Evaluate angular variation of each light source in 8 directions. Simulations are run on Colin27 brain models with nine virtual brain tumours constructed from GBM images from the cancer imaging archive. Analyze the volume of 100% dose for grey, white matters and tumour using a random combination of deviated directions for each light source for each model. Results & Conclusions The final result is on average less desirable than the nominal due to uncertainty in positions. The next steps for this work is to summarize a pattern for each tumour model and to find a way of improving the PDT-SPACE optimization algorithm that is more robust to position uncertainty.
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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 | 0.000 | 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".