National Reachback Systems for Nuclear Security: State-of-play report: ERNCIP Thematic Group Radiological and Nuclear Threats to Critical Infrastructure: Deliverable of task 3.1b
Bibliographic record
Abstract
Operational systems for nuclear security in Finland, France, Denmark, UK, US and Canada were reviewed. The Finnish case is a holistic approach to Nuclear Security Detection Architecture, as defined by the International Atomic Energy Agency; reachback is only one\ncomponent of the system, albeit an important crosscutting element of the detection architecture. The French and US studies concentrate on the reachback itself. The Danish nuclear security system is information-driven, relying on the cooperation of the competent authorities. The British and Canadian analyses describe nuclear security planning and operations in a Major Public Event (MPE), Olympics, where cooperation between the frontline officers and the reachback centre plays a key role to reduce radiological and nuclear risks.\nFor the implementation of an efficient reachback system there is a strong need for standardizing the data acquisition, storing, and the final distribution of the analysis results. Major nuclear powers take this activity very seriously and they have 24/7 all year national service for information processing. The case studies of Finland and France show that efficient European reachback is manageable and technically possible on a country-wide basis. The case study on Denmark reveals that countries with limited reachback resources need an adequate and standardized technical information sharing mechanism to aid their national analysis services in a precise and timely manner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".