Measuring Workload with Paired Detectors
Why this work is in the frame
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Bibliographic record
Abstract
Linear accelerator workloads for each available photon energy are important quantities to know for radiation safety considerations, and presented is a technique to measure the workload using paired detectors. The signals from the two detectors can give sufficient information to separate the signal contributions from 6 and 18 MV photon fields and, combined with a signal-per-monitor-unit calibration factor, yields the number of monitor units delivered for each energy. CR-39 NTD is a neutron detector chosen for its ability to discriminate between 6 MV and 18 MV radiation fields. TLD-100 is a detector responsive to both 6 MV and 18 MV fields. These appeared to be a good choice for a detector pair. This experiment had both failures and successes to report. The CR-39 NTD and TLD-100 were not a successful pairing. The CR-39 NTD signals saturated under this experiment's exposure conditions. The TLD-100 had a combination of detector noise and detector sensitivity that made extracting the 6 MV signal from the total signal impractical, unless the total exposure was overwhelmingly 6 MV. Nevertheless, the TLD-100 proved to be excellent for determining workloads when it was exposed to a single energy with 1% accuracy and 3% precision. The theory and data analysis showed the importance of understanding the noise contributions for the more general problem of pairing any two detector types. This experiment indicated the TLD-100 could be an excellent detector choice if paired with a suitable second detector.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it