Session1. Opening and Overview – Paper S1-1 Overview of SARNET Deployment and Progress
Bibliographic record
Abstract
their capacities of research in order to resolve the most important remaining uncertainties for enhancing, in regard of Severe Accidents (SA), the safety of existing and future Nuclear Power Plants (NPPs). This project has been defined in order to optimise the use of the available means and to constitute sustainable research groups in Europe and in Canada. SARNET tackles the fragmentation that exists between the different R&D national programmes, in defining common research programmes and developing common computer tools and methodologies for safety assessment. To reach these objectives, all the organizations networked in SARNET contribute to a so-called Joint Programme of Activities (JPA), which consists in: • Implementing an advanced communication tool for accessing all project information, fostering exchange of information, and managing documents; • Harmonizing and re-orienting the research programmes; • Jointly analysing the experimental results provided by research programmes in order to elaborate a common understanding of relevant phenomena; • Developing the integral computer code on severe accidents ASTEC, which capitalizes
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.232 | 0.134 |
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".