Fabricated Ge-doped flat optical fibres: Assessing the thermoluminescence glow curves for proton beam irradiation
Bibliographic record
Abstract
We investigate the fundamental characteristics of thermoluminescence (TL) glow curves on the fabricated 2.3 and 6.0 mol% germanium (Ge) doped flat optical fibres subjected to proton beam irradiation. The novel fabricated flat Ge-doped optical fibres used in this study were manufactured using a modified chemical vapour deposition (MCVD) based technique. TLD-100 dosimeters and commercial optical fibres (CorActive High-Tech Inc., Canada) were employed to allow for comparable TL response of the fabricated flat optical fibres. The proton beam irradiations were carried out using a 150-MeV proton beam energy over the radiation doses in the range from 1 to 5 Gy. A Harshaw™ 3500 TLD reader was used to read out the given radiation dose to the samples. The results show that the general structure of the TL glow curve for the fabricated flat optical fibres remains unchanged independently within the investigated radiation dose range. Apparently, the fabricated 2.3 mol% Ge-doped flat optical fibres have the most ideal TL glow curves characteristic, representing a single peak distribution, whereas the double peaks distributions were observed for a 6.0 mol% Ge-doped flat optical fibre. All optical fibres were considerably high glow peak temperatures that suggesting the presence of deep-trapped electrons. This convenient position at relatively high temperature will open the way for such optical fibres to be used not only in proton radiotherapy dosimetry, but also in high temperature and difficult-to-access areas, such as that of nuclear power plants.
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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) | 0.001 | 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 | 0.001 | 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".