Special Nuclear Material Identification Through One-Minute Measurement with a New Backpack Radiation Device in Real Scenario Conditions
Bibliographic record
Abstract
The constant concerns in global nuclear safety, aimed at deterring and combating the illicit trafficking of Material Out of Regulatory Control (MORC) and its possible use in criminal acts has raised the necessity of new detection solutions with higher efficiency and resolution to provide a high level of accuracy in the report to the authorities. Today’s radioactive isotope identifiers perform gamma spectroscopy identification and, sometimes, neutron counting. This paper presents the results of measurements performed in real-scenario conditions with a new type of portable radioactive isotope identifier for the detection and identification of both gamma and neutron sources. Its singular features are: 1) the capability to identify sources through the detection of neutrons, discriminating spontaneous fission sources (Cf-252), α-n sources (Am/Be, Am/Li) and nuclear material containing mix of isotopes of plutonium or uranium 2) the capability to make cross correlation between gamma and neutron measurements to achieve a higher level of accuracy in the identification of SNM that emits both neutrons and characteristics gammas. The test results are compared with international standards. The device exceeds the standard performance by triggering a neutron alarm for a 20.000 n/s Cf-252 source at a five times greater distance than the ANSI N42.34 one.
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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 | 0.000 |
| 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 | 0.000 | 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".