A CARBON NANOTUBE-BASED RADIATION SENSOR
Bibliographic record
Abstract
Dosimetric measurements and monitoring play an essential role in radiotherapy. Because of their sensitivity and relatively flat energy response ionization chambers remain the most important dosimeters. However, ionization chambers usually have large physical dimensions and require high bias voltages to achieve acceptable ionization collection efficiency. Such disadvantages limit their applications for in vivo dose measurements. The availability of novel materials such as carbon nanotubes (CNTs) has created the potential to miniaturize traditional ionization chambers and lower the bias voltages. This paper describes a new CNT-based radiation sensor. In the first stage, characteristics of the sensor were examined with two stainless steel electrodes. The sensor displayed excellent linear responses to exposure and showed accurate responses to oblique incident beam measurements. These experimental results showed that the prototype sensor is suitable for studying the ionization collection efficiency of CNTs. In the second stage, square- and irregular-shaped CNTs electrodes were designed. Saturation characteristics of the sensor with the CNTs electrodes were measured. Experimental results and ongoing work are presented and discussed in this paper.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".