Reconstruction of the Spatial Distribution of Surface Activity Concentration for an In-Situ, Gamma-Ray, Truck-Borne Survey
Bibliographic record
Abstract
In 2012, three test detonations of a radiological dispersal device (RDD) were performed at the experimental proving ground of Defence Research and Development Canada (DRDC) in Suffield, Alberta.These were the first outdoor detonations of a radioactive source in an outdoor environment.The purpose of these exercises was to characterize the effects of an RDD in the uncontrolled environment, so as to properly model the contamination as it would likely appear in the real situation of a terrorist attack.For example, wind transport affects the plume deposition distribution.A number of government research teams were involved in the experiments.The RDD source was 140 La.A suite of in-situ instruments were set up to monitor the blast dynamics and the plume deposition distribution.The Nuclear Emergency Response Team (NERT) of Natural Resources Canada performed two mobile surveys of the plume distribution to reconstruct a map of the spatial distribution of surface activity concentration at the time of the blast.One of these was an airborne survey, which involves using detectors of thallium-activated sodium iodide (Na(Tl)) to measure the count rate of gamma emissions from the distributed source.The survey provides a detailed map of the surface activity concentration, but only based on estimations associated with large spatial resolution.To improve on this, the truck-borne survey is essential because its sensitivity is confined to a more localized area of space, and its detection system is directional (it is called a directional spectrometer).With four standing crystals of NaI(Tl), this detection system offers data that, with the aid of Monte Carlo, can be used to reconstruct an averaged measure of the local surface activity concentration around the survey path of the truck.Using the Electron Gamma Shower code of the National Research Council of Canada (EGSnrc), the sensitivity of the truck-borne spectrometer was determined for finite disc sources of successively increasing size.The asymptote value of the sensitivity was used in a conversion factor to scale all the count rate values of the truck path into average values of the surface activity concentration.The result of I would like to acknowldege my supervisor, Dr. Laurel Sinclair, for her excellent advice, and for her encouragement to pursue innovative approaches.Also, particular thanks to members of the NERT for allowing me to participate in their activities and to conduct: data analysis meetings; field work; training; a conference, and exercises.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".