SU‐GG‐T‐271: Design and Study of a Novel Dosimeter Based On Carbon Fiber Material
Bibliographic record
Abstract
Purpose: To design the new generation of dosimeters that incorporate carbon fiber materials as sensing components for dosimetric measurements in radiotherapy. Method and Materials: A carbon fiber dosimeter mainly consists of a carbon fiber sheet as sensing material and two PMMA slices as holders. The carbon fiber sheet was sandwiched between the two PMMA holders, each having a hole with 1.8 × 1.8 cm2 dimension. Copper electrodes were made on one PMMA holder to make electrical contacts. The dosimeter was connected to a resistor array in serial. A Dose 1 digital electrometer was used to measure signals output from the dosimeter in real‐time. Both 6 and 15 MV photon beams generated from a Varian Clinac 21 EX medical linear accelerator were used to test the dosimeter. Radiation dosimetric measurements were carried out by varying the dose rates, total dose, and field sizes to characterize various properties of the dosimeter. Results: This carbon fiber dosimeter responded to different ionizing radiation beams with a change in current amplitude. For both 6 and 15 MV photon beams, when dose rate was varied from 100 to 600 MU/min, the current changes measured by the dosimeter increased. The similar results were observed in diamond dosimeters. When the dosimeter was irradiated with total dose range from 100 to 600 MUs for 6 MV photon beams, excellent linear responses were displayed. The dosimeter measured increase signals with field size increased from 0.5 × 0.5 cm2 to 1.8 × 1.8 cm2. Conclusion: The carbon fiber dosimeter displayed excellent linear responses to total dose and was able to provide real‐time information on dose and dose rate at the same time. The dosimeter is expected to offer a higher spatial resolution by miniaturizing the physical size of the carbon‐based dosimeter design.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".