Test of a bubble passive spectrometer for neutron dosimetry
Bibliographic record
Abstract
A passive system for neutron spectrometry has been tested in view of neutron dose evaluation in mixed radiation fields. This system, based on bubble detectors (Bubble Technology Industries, Ontario, Canada), is suitable to evaluate the neutron energy distribution in the range 10 keV-20 MeV even in the presence of intense gamma radiation, as required in various fields: medical x-ray accelerators, nuclear reactors, cosmic ray exposures on commercial high-altitude flights and space missions. A new unfolding code BUNTO has been especially developed for this application. In the present work, the results of two experimental tests are summarized. In the first one, the device has been exposed to a standard AmBe neutron source (Joint Research Centre, Ispra, Varese, Italy). In the second one, measurements have been carried out at the MAX-Lab photonuclear facility in Sweden, with a bremsstrahlung photon beam impinging on thick targets of different materials and generating a giant dipole resonance neutron spectrum. Simulations of the experimental apparatus have been performed with MCNP4B (AmBe source) and with MCNP4B-GN (MAX-Lab). Results of the comparison between experimental and calculated spectra are shown and discussed. A good agreement between measurements and simulation data is obtained in both the experiments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".