Comment on "The Clinical Features and Pathophysiology of Acute Radiation Dermatitis in Patients Receiving Tomotherapy"
Bibliographic record
Abstract
We read with interest the article by Lee et al. 1, where a significantly more severe dermatitis was reported in patients receiving tomotherapy when compared to patients receiving conventional radiation. However, the authors do not provide any reasons for their findings. Unfortunately, there is no information on contouring of the planning target volume (PTV); therefore, we can only speculate that grade 2 dermatitis in breast cancer patients might occur due to inclusion of voxels with low computer tomography (CT) numbers (air) as the target. Low density materials are less attenuating and require higher intensity of radiation for delivery of the same dose as to more dense tissues. If this is the case, the actual dose delivered to the surface layer might be higher than the prescription. In our institution, tomotherapy has been used clinically since September 2004, and we have not observed serious dermatitis in our tomotherapy patients, compared to “conventional” techniques. In order to verify the correspondence of calculated and actually delivered doses, either MOSFET dosimeters OneDose TM
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.023 | 0.021 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".