Feasibility of bulk explosives detection using photoneutron spectroscopy
Bibliographic record
Abstract
Research has been conducted since the 1950s on nuclear methods to confirm the presence of bulk explosives by detecting characteristic emitted radiation. In most practical situations, penetrating radiation is required, which restricts the problem to gamma rays and neutrons. The most successful reactions to date has been radiative thermal neutron capture (thermal neutron analysis) and prompt radiative emission following inelastic fast neutron scattering (fast neutron analysis). An alternative to these neutron-in, gamma ray-out reactions is photoneutron production. A gamma ray whose energy exceeds the threshold for neutron production in a particular atomic nucleus can cause a neutron to be emitted. For a given isotope and assuming monoenergetic photons, the emitted neutrons will have a spectrum consisting of one or more discrete energies. If the gamma ray source and neutron spectrometer are appropriately chosen, the neutron spectrum can be used as a fingerprint to identify the isotope. This photoneutron spectroscopy method has a number of potential advantages over thermal and fast neutron analysis, such as generally simpler spectra and low inherent natural neutron background. It also has drawbacks, such as possible induced neutron background and a present lack of suitable fieldable photon sources. This paper will describe the method and preliminary simulations and calculations to examine its feasibility. Possible sources, detectors and geometries will be discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".