ABSTRACT RADIOACTIVE WASTE MANAGEMENT POLICY IN ROMANIA
Bibliographic record
Abstract
Radioactive waste management is a key issue of the environmental policy of our company. According to the Romanian Nuclear Act (Law 111/1996) and the Law of the Environmental Protection (Law 137/1996) the owner is responsible for the management of all radioactive wastes streams at the Nuclear Power Plant, including the technical and cost components. For radioactive waste disposal and plant decommissioning is under examination a new law setting up a National Fund paid by all users of nuclear energy which are producing radwastes. To meet these legal provisions, NUCLEARELECTRICA developed a radioactive waste management policy, which incorporate the practice in the country of the plant supplier (Canada) and the recommendations of IAEA and European Commission. The policy established objectives and targets are accordance with the status of Cernavoda NPP project. On short term, the priorities of our radioactive waste management policy are to extend the spent fuel storage capacity using the dry storage technology and to upgrade the LILW characterization process in order to provide necessary data for selection of treatment/conditioning technologies. On long term our policy includes a facilities for LILW packaging for disposal in new surface repository to be built on the Cernavoda NPP site. For HLW the interim storage for about 50 years will provide the necessary time to select and implement the geological disposal, in accordance with the best international practice.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".