Determination of consensus <i>k</i> <sub> <i>Q</i> </sub> values for megavoltage photon beams for the update of IAEA TRS-398
Bibliographic record
Abstract
Abstract The IAEA is currently coordinating a multi-year project to update the TRS-398 Code of Practice for the dosimetry of external beam radiotherapy based on standards of absorbed dose to water. One major aspect of the project is the determination of new beam quality correction factors, k Q , for megavoltage photon beams consistent with developments in radiotherapy dosimetry and technology since the publication of TRS-398 in 2000. Specifically, all values must be based on, or consistent with, the key data of ICRU Report 90. Data sets obtained from Monte Carlo (MC) calculations by advanced users and measurements at primary standards laboratories have been compiled for 23 cylindrical ionization chamber types, consisting of 725 MC-calculated and 179 experimental data points. These have been used to derive consensus k Q values as a function of the beam quality index TPR 20,10 with a combined standard uncertainty of 0.6%. Mean values of MC-derived chamber-specific <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mi>f</mml:mi> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">c</mml:mi> <mml:mi mathvariant="normal">h</mml:mi> </mml:mrow> </mml:mrow> </mml:msub> </mml:math> factors for cylindrical and plane-parallel chamber types in 60 Co beams have also been obtained with an estimated uncertainty of 0.4%.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".