Assessment of RepU Recycling Contribution to ESG Performance in French Nuclear Power Plant with a LCA “Pilot Study”
Bibliographic record
Abstract
Although nuclear energy is acknowledged for its low CO2 emission, the fuel cycle front-end footprint can be further decreased through the use of recycled nuclear material resulting from spent fuel reprocessing.This paper presents a typical case of footprint reduction obtained with the use of Reprocessed Uranium (RepU) in Cruas French Nuclear Power Plant.The demonstration is based on a Life Cycle Assessment (LCA) screening study, also called "pilot study" in the paper, realized following LCA general method with Simapro LCA software and ecoinvent 3.6 Database.Its main result is a significant decrease of climate change indicator (around 40%) compared to the 2022 EDF nuclear kWh LCA study.The calculation was extended by integrating two other LCA indicators, "particle matter/respiratory inorganics" and "resource depletion", for exploratory purposes.This pilot study will be improved as new data become available, with the purpose to lead to a standardized LCA study.It will also be a tool to identify and to quantify ways to further reduce RepU fuel cycle environmental footprint.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".