SU‐C‐304‐06: Determination of Intermediate Correction Factors for Three Dosimeters in Small Composite Photon Fields Used in Robotic Radiosurgery
Bibliographic record
Abstract
Purpose: To calculate using Monte‐Carlo the intermediate and total correction factors (CFs) for two microchambers and a plastic scintillator for composite fields delivered by the CyberKnife system. Methods: A linac model was created in BEAMnrc by matching percentage depth dose (PDD) curves and output factors (OFs) measured using an A16 microchamber with Monte Carlo calculations performed in egs_chamber to explicitly model detector response. Intermediate CFs were determined for the A16 and A26 microchambers and the W1 plastic scintillator in fourteen different composite fields inside a solid water phantom. Seven of these fields used a 5 mm diameter collimator; the remaining fields employed a 7.5 mm collimator but were otherwise identical to the first seven. Intermediate CFs are reported relative to the respective CF for a 60 mm collimator (800 mm source to detector distance and 100 mm depth in water). Results: For microchambers in composite fields, the intermediate CFs that account for detector density and volume were the largest contributors to total CFs. The total CFs for the A26 were larger than those for the A16, especially for the 5 mm cone (1.227±0.003 to 1.144±0.004 versus 1.142±0.003 to 1.099±0.004), due to the A26's larger active volume (0.015 cc) relative to the A16 (0.007 cc), despite the A26 using similar wall and electrode material. The W1 total and intermediate CFs are closer to unity, due to its smaller active volume and near water‐equivalent composition, however, 3–4% detector volume corrections are required for 5 mm collimator fields. In fields using the 7.5 mm collimator, the correction is nearly eliminated for the W1 except for a non‐isocentric field. Conclusion: Large and variable CFs are required for microchambers in small composite fields primarily due to density and volume effects. Corrections are reduced but not eliminated for a plastic scintillator in the same fields.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".