The roles of power loss and momentum-pressure loss in causing particle-detachment in tokamak divertors: I. A heuristic model analysis
Bibliographic record
Abstract
Abstract Particle-detachment is defined here based on Loarte’s Degree of Detachment , quantifier (1998 Nucl. Fusion 38 331). Specifically, particle-detachment is defined to be the edge plasma regime that sets in on an edge flux-tube when the plasma flux density onto the divertor target, Γ t , starts to increase less than quadratically with n u , the plasma particle density in the flux tube upstream of the divertor. A simple heuristic model that includes volumetric loss of both pressure-momentum, p total , and parallel power flux density in the flux tube, q ∣∣ , is used to explicitly demonstrate that, generically , both types of volumetric loss are required for particle-detachment to occur. The principle conclusion of this paper is that it is the combination of momentum-loss and power-loss that is the cause of particle-detachment and that therefore any attribution of particle-detachment to just one of these volumetric loss processes, or any assignment of paramountcy to one type of loss over the other, as sometimes may appear to occur, would not be appropriate.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".