WE‐D‐T‐617‐06: Development of a Sealed Water Calorimeter for Clinical Electron Beams
Bibliographic record
Abstract
Purpose: The purpose of this project is to develop a water calorimeter for use in clinical electron beams to directly determine absorbed dose to water. This work presents the design of the Electron Sealed Water (ESW) calorimeter, preliminary measurements and evaluation of correction factors. Method and Materials: The calorimeter contains a 30 × 30 × 20 cm3 water phantom surrounded by a cooling system to allow for operation at 4°C. Two thermistor probes measure the temperature change inside a glass vessel filled with high‐purity nitrogen‐saturated water. Correction factors for the glass perturbation were calculated using Monte‐Carlo simulations. Corrections for thermal conduction were simulated using Femlab finite element modeling software. Resistance of the thermistor probes was measured using a lock‐in amplifier and an AC bridge circuit. Measurements were done for 6, 9, 12, 16 and 20 MeV electron beams from a Varian Clinac 21EX with a 10 × 10 cm2 applicator at 105.5 cm SSD with the thermistor probes positioned at dref. Irradiations of 667 MU were done at 1000 MU/min for an irradiation time of 40 s. Measurements were also taken with a PTW Roos ion chamber inside the calorimeter phantom. Results: The standard error on the mean temperature change for each energy was less than 0.2%. Reproducibility for measurements on separate occasions was 0.2%. When normalized to the 12 MeV measurements, values of k'R‐50 for the Roos chamber calculated from calorimeter measurements for the 9, 16 and 20 MeV beams and agreed with TG‐51 values within 0.7 %. Conclusion: Water calorimetry in electron beams has previously been regarded as unfeasible as high gradients were thought to provoke unmanageable temperature gradients. Using the ESW calorimeter, we have shown for the first time that reproducible measurements can be performed in electron beams with energies as low as 6 MeV.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".