Bibliographic record
Abstract
It is fair to say that the clinical determination of absorbed dose in a high‐energy photon beam is the only situation where there is currently a direct chain of traceability from the standards laboratory to the end‐user and the protocol requires only ‘simple’ conversion/ correction factors. For all other modalities the primary standard is in a different quantity (e.g., air kerma) or in the right quantity but a different radiation beam (e.g., for proton dosimetry) from what is required for the clinical dose delivery. Complex conversion factors are often then required in applying protocols to give the desired final quantity. Such conversion factors can be from kerma to dose (in the case of kilovoltage x‐rays or brachytherapy) or from one type of radiation beam to another (in the case of electron or proton beams). Even non‐standard MV photon beams (e.g. non‐standard geometry, presence of a magnetic field) can have a significant impact on the procedure that must be followed compared to what is found in TG‐51. While national and international bodies, such as the AAPM and the IAEA, primarily address the end‐user's needs with protocols and guidelines, calibration laboratories are developing new measurement standards and approaches that should simplify the calibration chain and therefore lead to simpler, more robust procedures to yield absorbed dose in the beam of interest in the radiation therapy clinic. This session will provide a broad overview of the worldwide developments currently in progress, and also planned for the near future, of absorbed dose standards for a range of beam modalities including: Proton beams HDR and LDR brachytherapy Non‐standard photon fields (small fields, impact of magnetic fields, etc) Learning Objectives: Understand the present traceability chain for all beam modalities in regular use in the radiation therapy clinic. Understand the current and planned development of absorbed dose standards for modalities other than linac photon beams. Understand the physical basis of these standards and the potential impact on end‐user dosimetry. Understand the likely impact of these standards developments on dosimetry protocols in the coming 5–10 years.
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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 | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.037 | 0.040 |
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".