106 “Resilience by Design” - Description of a Pilot Radiation Oncology Wellness Program
Bibliographic record
Abstract
CARO-ASM 2019 33.3%.The most common tumour locations were the convexity of the brain (39.5%) and base of skull (30.9%).Tumour size ranged from 0.1 to 51.8 cc (median = 4.3 cc).The median PTV volume was 5.9 cm 3 and median prescription isodose line was 75%.Total dose ranged from 14 to 25 Gy in 1 to 5 fractions, with the most common schedule being 18 Gy in 3 fractions (35.8%).Treatment was completed as planned in 98.6% of patients.After a median follow-up of 50 months, crude local control rate was 97.5%.Fiveyear OS and PFS were 93.9% and 90.7%, respectively.Overall, the late Grade III/IV toxicity rate was 2.7%.Radionecrosis rate was 6.2%, with 60% of cases being symptomatic necrosis.One patient had a surgical resection and the others were managed conservatively with corticosteroids.The median time from treatment completion to radionecrosis presentation was seven months.There were no deaths attributable to ICM or treatment-related complications.Conclusions: Based on the data from our centre, SRS remains a safe modality to treat low-grade ICM with acceptable long-term toxicity and radionecrosis rates.Efficacy is similar to conventional fractionation and even larger lesions may be treated with a hypofractionated course.SRS should be offered to patients who are not ideal surgical candidates, for recurrent disease, and for those who wish to avoid an invasive operation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".