On the correction, perturbation and modification of small field detectors in relative dosimetry
Bibliographic record
Abstract
The purpose of this study was to derive a complete set of correction and perturbation factors for output factors (OF) and dose profiles. Modern small field detectors were investigated including a plastic scintillator (Exradin W1, SI), a liquid ionization chamber (microLion 31018, PTW), an unshielded diode (Exradin D1V, SI) and a synthetic diamond (microDiamond 60019, PTW). A Monte Carlo (MC) beam model was commissioned for use in small fields following two commissioning procedures: (1) using intermediate and moderately small fields (down to 2 × 2 cm(2)) and (2) using only small fields (0.5 × 0.5 cm(2) -2 × 2 cm(2)). In the latter case the detectors were explicitly modelled in the dose calculation. The commissioned model was used to derive the correction and perturbation factors with respect to a small point in water as suggested by the Alfonso formalism. In MC calculations the design of two detectors was modified in order to minimize or eliminate the corrections needed. The results of this study indicate that a commissioning process using large fields does not lead to an accurate estimation of the source size, even if a 2 × 2 cm(2) field is included. Furthermore, the detector should be explicitly modelled in the calculations. On the output factors, the scintillator W1 needed the smallest correction (+0.6%), followed by the microDiamond (+1.3%). Larger corrections were observed for the microLion (+2.4%) and diode D1V (-2.4%). On the profiles, significant corrections were observed out of the field on the gradient and tail regions. The scintillator needed the smallest corrections (-4%), followed by the microDiamond (-11%), diode D1V (+13%) and microLion (-15%). The major perturbations reported were due to volume averaging and high density materials that surround the active volumes. These effects presented opposite trends in both OF and profiles. By decreasing the radius of the microLion to 0.85 mm we could modify the volume averaging effect in order to achieve a discrepancy less than 1% for OF and 5% for profiles compared to water. Similar results were observed for the diode D1V if the radius was increased to 1 mm.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".