Evaluation of a novel 4D <i>in vivo</i> dosimetry system
Bibliographic record
Abstract
A prototype of a new 4D in vivo dosimetry system capable of simultaneous real-time position monitoring and dose measurement has been developed. The radiation positioning system (RADPOS) is controlled by a computer and combines two technologies: MOSFET radiation detector coupled with an electromagnetic positioning device. Special software has been developed that allows sampling position and dose either manually or automatically in user-defined time intervals. Preliminary tests of the new device include a dosimetric evaluation of the detector in 60Co, 6 MV, and 18 MV beams and measurements of spatial position stability and accuracy. In addition, the effect of metals and other materials on the performance of the positioning system has been investigated. Results show that the RADPOS system can measure in-air dose profiles that agree, on average, within 3%-5% of diode measurements for the energies tested. The response of the detector is isotropic within 1.6% (1 SD) with a maximum deviation of +/- 4.0% over 360 degrees. The maximum variation in the calibration coefficient over field sizes from 6 x 6 to 25 x 25 cm2 was 2.3% for RADPOS probe with the high sensitivity MOSFET and 4.6% for the probe with the standard sensitivity MOSFET. Of the materials tested, only aluminum, lead, and brass caused shifts in the RADPOS read position. The magnitude of the shift varied between materials and size of the material sample. Nonmagnetic stainless steel (Grade 304) caused a distortion of less than 2 mm when placed within 10 mm of the detector; therefore, it can provide a reasonable alternative to other metals if required. The results of the preliminary tests indicate that the device can be used for in vivo dosimetry in 60Co and high-energy beams from linear accelerators.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".