Special Section: CNS's 8th International Conference on Simulation Methods in Nuclear Science and Engineering
Bibliographic record
Abstract
Adriaan Buijs, Conference ChairThe eighth edition of the International Conference on Simulation Methods in Nuclear Science and Engineering was organized by the Canadian Nuclear Society and held in Ottawa, ON, Canada in October, 2018. The Conference is organized every three years. It is customarily preceded by a day of technical seminars or workshops and followed by a one-day technical tour of one of Canada's nuclear research facilities or Universities. The Conference attracts an international audience of researchers and practitioners from industry, academia, and government who are interested in the latest developments around numerical simulation and related topics in nuclear science and engineering.Eleodor Nichita, Technical-Program ChairThe 2018 edition of the Conference attracted approximately 80 participants. Close to 60 technical papers were presented, together with ten plenary presentations. It was preceded by a day of workshops dedicated to state-of-the art nuclear simulation computer codes such as DRAGON, SuperMC, SCALE, and COBRA-TF; and followed by a tour of the Canadian Nuclear Laboratories (CNL) in Chalk River, ON, Canada's Flagship Nuclear Laboratory. CNL is the prospective host of four SMR demonstration facilities and also hosts world-class fuel manufacturing and testing facilities. It also operates a fuel testing reactor, ZED-2.Technical presentations were grouped in several tracks: thermal-hydraulics and safety; reactor physics, plant operation, Monte Carlo methods; and modeling and simulation. Given the high level of interest elicited by some of the technical presentations, a selected group of authors were given the opportunity to expand their original contributions to the conference by preparing full-length papers and to publish them in this special section of the Nuclear Engineering and Radiation Science Journal.The Canadian Nuclear Society and the organizers of the conference are grateful to the American Society of Mechanical Engineers and to the editorial board of its Journal of Nuclear Engineering and Radiation Science for making this excellent platform available for the dissemination of technical results from the Conference. The guest editors of this Special Section want to thank the authors and reviewers for their contributions and for the hard work that went into producing this section. This Special Section and, indeed, this Journal are only made possible by your vital contributions.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.167 | 0.084 |
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".