An experimental and computational investigation of the standard temperature‐pressure correction factor for ion chambers in kilovoltage x rays
Bibliographic record
Abstract
For ion chambers with cavities open to the surrounding atmosphere, the response measured at a given temperature and pressure must be corrected using the standard temperature-pressure correction factor (P(TP)). A previous paper based solely on Monte Carlo simulations [D. J. La Russa and D. W. O. Rogers, Med. Phys. 33, 4590-4599 (2006)] pointed out the shortcomings of the P(TP) correction factor when used to correct the response of non-air-equivalent chambers for low-energy x-ray beams. This work presents the results of several experiments that corroborate these calculations for a number of ion chambers. Monte Carlo simulations of the experimental setup revealed additional insight into the various factors affecting the extent of the breakdown of P(TP), including the effect of impurities and the sensitivity to chamber dimensions. For an unfiltered 60 kV beam, the P(TP)-corrected response of an NE 2571 ion chamber measured at 0.7 atm was 2.5% below the response measured at reference conditions. In general, Monte Carlo simulations of the experimental setup using EGSnrc were within 0.5% of measured values. EGSnrc-calculated values of air kerma calibration coefficients (N(K)) at low x-ray energies are also provided as a means of estimating the level of impurities in the chambers investigated. Calculated values of N(K) normalized to the value measured for a 250 kV beam were obtained for three chambers and were within 1% of experiment with one exception, the Exradin A12 in a 50 kV beam.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".