SU‐E‐T‐156: Can Sr‐90 Check Sources Replace Co‐60 Measurements for Monitoring of Reference Chamber Stability?
Bibliographic record
Abstract
Purpose: To determine the ultimate precision of a system for monitoring reference‐class ion chamber stability using a commercial Sr‐90 check source. Methods: A detailed investigation of a commercial Sr‐90 check source (PTW48002) was carried out using a series of Farmer‐type ionization chambers. Investigations included: positioning repeatability (angular variation as chamber is rotated in source, variation in ionization current with vertical alignment); chamber settling; short and long term repeatability Results: i) Measurement precision – the ionization current was typically 10 pA, and therefore a high‐precision electrometer is required to prevent electrometer noise/resolution/leakage biaising the results. ii) Chamber settling ‐ the chamber response stabilizes after approximately 10 minutes, which is longer than reported for linac beams and is likely due to the low doserate of the source.iii) The measured response depended at the 1 % level on the orientation of the chamber with respect to the source. However, consistent positioning resulted in repeatability at the 0.05 % level. Care was also required to ensure that the chamber was consistently positioned vertically with respect to the source. The sensitivity to vertical position was found to be > 1 % per mm.iv)With a uniform procedure the long‐term (> 6 month) repeatability was found to be better than 0.1 % for multiple chamber types and potentially a precision of 0.05 % is achievable. Conclusion: A Sr‐90 check source is easy to use and is a viable alternative to Co‐60 for monitoring reference chamber stability.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".