Scrape-off layer properties of ITER-like limiter start-up plasmas in JET
Bibliographic record
Abstract
Recent experiments at JET combining reciprocating probe measurements upstream and infrared thermography at the plasma-facing components (PFC) on plasmas in limiter configurations show that the common approach to predicting the power load on the limiter underestimates the heat flux at the contact point by a factor 1.5–3. The current model and scaling laws used for predicting the power load onto the first wall during limiter current ramp-up/down in ITER are uncertain and a better understanding of the heat transport to the PFCs is required. The heat loads on PFCs are usually predicted by projecting the parallel heat flux associated with scrape-off layer (SOL) properties at the outer mid-plane (upstream) along the magnetic field lines to the limiter surface and deducing the surface heat flux through a cosine law, thus ignoring any local effect of the PFC on transport within the SOL. The underestimate of the heat flux is systematic in inner wall limiter configurations, independent of the plasma parameters, whereas in outer limiter configuration this is not observed, probably because of the much shorter SOL power decay length. Models that can explain this enhanced heat flux around the contact point are proposed and discussed although no definitive conclusion can be drawn.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".