The suitability of large area drift chambers as the technology choice for the cosmic ray inspection and passive tomography (CRIPT) project
Bibliographic record
Abstract
The CRIPT project brings together several Canadian institutions, concerned with the detection of Special Nuclear Materials (SNM), addressing a requirement at ports-of-entry for detection of SNM in the many thousands of containers that flow into and out of Canada every day, while at the same time providing a way of monitoring the contents of nuclear waste storage containers, for waste management and non-proliferation reasons. The scale of these applications is large - typically tens of cubic metres, requiring detectors that can cover a large area at a minimum cost. The CRIPT project considered drift chambers adapted from high energy physics experience, as one of its technology choices. We report here on the performance of a full scale prototype, which covers an area of 2.4m × 1.2m with only 6 readout channels, and provides a 2D data point with accuracies (in x and z) of around 2 mm.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".