Atmospheric Neutron Monitoring through Optical Fiber-Based Sensing
Bibliographic record
Abstract
The potential of fiber-based sensors to monitor the fluence of atmospheric neutrons is evaluated through accelerated tests at the TRIUMF Neutron Facility (TNF) (BC, Canada), offering a flux approximatively 109 higher than the reference spectrum observed under standard conditions in New York City, USA. The radiation-induced attenuation (RIA) at 1625 nm of a phosphorus-doped radiation sensitive optical fiber is shown to linearly increase with neutron fluence, allowing an in situ and easy monitoring of the neutron flux and fluence at this facility. Furthermore, our experiments show that the fiber response remains sensitive to the ionization processes, at least up to a fluence of 7.1 × 1011 n cm−², as its radiation sensitivity coefficient (~3.36 dB km−1 Gy−1) under neutron exposure remains very similar to the one measured under X-rays (~3.8 dB km−1 Gy−1) at the same wavelength. The presented results open the way to the development of a point-like or even a distributed dosimeter for natural or man-made neutron-rich environments. The feasibility to measure the dose caused by the neutron exposure during stratospheric balloon experiments, or during outer space missions, is presented as a case study of a potential future application.
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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 | 0.000 |
| 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".