Feasibility study of validating activation corrosion products calculations in cooling water loops at JET
Bibliographic record
Abstract
This paper presents the feasibility study for verifying the possibility to host an experiment in JET, during a future D-T campaign to validate calculation tools for predicting formation and migration of Activated Corrosion Products, generated by corrosion of base metals, in cooling loops of fusion experiment devices such as ITER. It has been estimated that Activated Corrosion Products inventory generated in an experimental loop with the test section under the neutron flux in a region close to the JET Vacuum Vessel, with the expected D-T campaign neutron fluence, were sufficient to produce a related measurable level in the ion exchange resin of that loop. A solution envisaged for hosting this loop is using vertical ports at the bottom of JET and its surrounding area. A general sketch of main elements required for constructing such a loop was drawn. The relevance for ITER is linked to its licensing, as the ACP radioactive inventory assessment has a two-fold relevance: (1) evaluating the mobilisable radioactive inventory in case of accidents and (2) assessing an important source of direct decay gamma irradiation to staff operating during routine maintenance. The envisaged loop in JET should include the most important materials in the ITER Primary Heat Transfer System loops (copper alloys and stainless steels).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".