Poster — Thur Eve — 57: Use of a Micro Liquid Ionization Chamber for Commissioning of Radiosurgery Beams
Bibliographic record
Abstract
A commercially available liquid ionization chamber (PTW, Freiburg, Germany) was used in the commissioning of stereotactic radiosurgery beams for a Novalis Tx linear accelerator. The chamber has a small collecting volume (0.002cm3) yet providing a relatively high signal for its size. The chamber was attached to a solitary electrometer for output measurements, and to a water scanning system for PDD and beam profile measurements. The commissioning set consisted of output factors, percentage depth doses and off‐axis beam profiles for six collimator sizes ranging from 4mm to 15mm in diameter. The measured data was compared to both Gafchromic film dosimetry measurements and to data from the literature. Output factors measured with the liquid ion chamber are in good agreement with film measurements (<2% difference, except for 3.8% difference for the 4mm collimator). Similar overall agreement was found with a recent publication by Fan et al.,(2009). Beam profile measurements were found to be in very good agreement with Gafchromic film measurements. Our PDD data was equally in reasonable agreement with data from a recent publication by Chang et al., (2008) with discrepancies of 2–3% observed. A comparison of TMRs calculated from our PDD data and from direct measurement revealed larger differences, increasing with depth, that have yet to be resolved. The liquid ion chamber was easy to use required only a brief pre‐irradiation to provide a stable signal. Our preliminary results suggest this high spatial resolution chamber has usefulness in small field measurements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".