Bibliographic record
Abstract
The International Nuclear Energy Research Initiative (I-NERI) supports the National Energy Policy by conducting research to advance the state of nuclear science and technology in the United States (U.S.). I-NERI sponsors innovative scientific and engineering research and development (R&D) in cooperation with participating countries. The R&D research performed under the I-NERI umbrella addresses the key issues affecting the future of nuclear energy and its global deployment. I-NERI research is directed towards improving cost performance, increasing proliferation resistance, enhancing safety, and improving the waste management of future nuclear energy systems. This I-NERI 2004 Annual Report serves to inform interested parties on the program's organization, progress of the collaborative research projects, and future planning for the program. The report covers the four years of I-NERI activity since the program's inception in fiscal year (FY) 2001. The motivation and series of events that led to the creation of the I-NERI program are discussed in Section 2. The participating countries in current I-NERI collaborative agreements are also presented. Section 3 presents an overview of the I-NERI goals and objectives, a work scope summary for the collaborative projects, and a summary of research project awards through the end of FY 2004. It also includes FY 2005 accomplishments and planned FY 2005 activities. A summary of programmatic accomplishments is presented in Section 4. Also included is a summary of new and existing projects, an overview of the I-NERI program funding, and the new collaborations anticipated in FY 2005. The R&D work scope for current I-NERI collaborative projects with Canada, France, Japan, the Organization for Economic Cooperation and Development/Nuclear Energy Agency (OECD/NEA), and the Republic of Korea are presented in Sections 5 through 9, respectively. For each participating country, an index of projects and a summary of FY 2004 technical accomplishments are presented in Appendices A through E.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.168 | 0.150 |
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".