Sci‐YIS Fri ‐ 05: Design and testing of a new sealed water calorimeter for electron beams
Bibliographic record
Abstract
The Electron Sealed Water (ESW) calorimeter is a new device designed for measurements in clinical electron beams. This work presents the calorimeter design, preliminary measurements and evaluation of correction factors. 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 temperature change inside a glass vessel filled with high‐purity nitrogen‐saturated water. Correction factors for glass perturbation were calculated using Monte Carlo simulations. Corrections for thermal conduction were simulated using Femlab 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. 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. For 30 runs, the standard error on the mean temperature change was less than 0.2% for all energies. 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 agreed with TG‐51 values within 0.7 %. Water calorimetry in electron beams has previously been regarded as unfeasible as high dose 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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".