Quality assurance of asymmetric jaw alignment using 2D diode array
Bibliographic record
Abstract
PURPOSE: A method using a 2D diode array is proposed to measure the junction gap (or overlap) and dose with high precision for routine quality assurance of the asymmetric jaw alignment. METHODS: The central axis (CAX) of the radiation field was determined with a 15 × 15 cm(2) photon field at four cardinal collimator angles so that the junction gap (or overlap) can be measured with respect to the CAX. Two abutting fields having a field size of 15 cm (length along the axis parallel to the junction) × 7.5 cm (width along the axis perpendicular to the junction) were used to irradiate the 2D diode array (MapCHECK2) with 100 MU delivered at the photon energy of 6 MV. The collimator was slightly rotated at 15° with respect to the beam central axis to increase the number of diodes effective on the measurement of junction gap. The junction gap and dose measured in high spatial resolution were compared to the conventional methods using an electronic portal imaging device (EPID) and radiochromic film, respectively. In addition, the reproducibility and sensitivity of the proposed method to the measurements of junction gap and dose were investigated. RESULTS: The junction gap (or overlap) and dose measured by MapCHECK2 agreed well to those measured by the conventional methods of EPID and film (the differences ranged from -0.01 to 0 cm and from -1.34% to 0.6% for the gap and dose, respectively). No variation in the repeat measurements of the junction gap was found whereas the measurements of junction dose were found to vary in quite a small range over the days of measurement (0.21%-0.35%). While the sensitivity of the measured junction gap to the actual junction gap applied was the ideal value of 1 cm∕cm as expected, the sensitivity of the junction dose to the actual junction gap increased as the junction gap (or overlap) decreased (maximum sensitivity: 201.7%∕cm). CONCLUSIONS: The initial results suggest that the method is applicable for a comprehensive quality assurance of the asymmetric jaw alignment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".