Sci‐Sat AM (2) Therapy‐01: A rotational total skin electron irradiation technique using a linear accelerator with a commercially available high dose rate total body electron mode
Bibliographic record
Abstract
We have transferred and modernized our 25‐year‐old rotational total skin electron irradiation (RTSEI) technique from a linac (Varian Clinac‐18) with a custom modified beam line to a linac (Varian 21EX) with a commercially available electron mode intended for total skin electron irradiation. The new technique uses a “high dose rate” mode and a “high dose per Monitor Unit” mode in conjunction with a custom‐made flattening filter to produce a uniform beam at an extended SSD of 378 cm. Reference dosimetry for the stationary and rotational electron fields was performed to allow delivery of the prescription dose using the linac's transmission ionization chamber. The accessory tray holds the custom‐made flattening filter and automatically selects the beam energy (6 MeV) and high dose rate (888 MU/min) while moving the collimators to the maximum 40 × 40 cm2 field size. Beam parameters are monitored using the record‐and‐verify (VARIS) system. Patients are treated on a rotating platform with a high dose rate electron beam having a zmax at the skin surface, an R50 at 15 mm and a bremsstrahlung contamination of the order of 3%. The nominal dose rate to water at zmax (surface) for the rotational technique was determined to be 24.1 cGy/1000 MU, and beam delivery is monitored with a secondary Farmer‐type ionization chamber located near the patient in the treatment field. Treatment times for a daily dose of 2.0 Gy are of the order of 9.5 minutes and to date we have treated 15 patients with this technique.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.007 |
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".