Poster — Thur Eve — 25: Improving the Accuracy of Electrometer Calibrations
Bibliographic record
Abstract
For many years, the Ionizing Radiation Standards (IRS) group, NRC, has maintained the capacity to calibrate high‐quality electrometers used for radiation therapy. In particular, electrometer calibrations have now become a necessary part of the recently introduced MV X‐ray calibration service. With a growing interest in electrometer calibrations, the IRS electrometer calibration facility was due for revamping and upgrading. In 2008, instability in the IRS electrometer calibration system was observed during a period of high humidity. Troubleshooting suggested that the high humidity was causing high leakage currents, but it was difficult to obtain evidence of leakage occurring at any specific location since the leakage currents were small (pA or even fA). Desiccation of the calibrated standard capacitors dramatically improved the overall system performance, so the eventual solution involved isolation of the calibrated standard capacitors using a humidity controlled cabinet. Additional improvements included changing most of the connectors in the system from coaxial BNC to two‐lug triaxial bayonet type (TRB), and designing a 3‐stage filter to allow calibrations of newer current‐based electrometers. The result is an electrometer calibration facility that is unaffected by humidity and very stable, allowing year‐round calibrations for any of the electrometer models commonly encountered.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".