Lower hybrid current drive experiments on Alcator C-Mod: Comparison with theory and simulation
Bibliographic record
Abstract
Lower hybrid (LH) current drive experiments have been carried out on the Alcator C-Mod tokamak [I. H. Hutchinson et al., Phys. Plasmas 1, 1511 (1994)] using a radio-frequency system at 4.6GHz. Up to 900kW of LH power has been coupled and driven LH currents have been inferred from magnetic measurements by extrapolating to zero loop voltage, yielding an efficiency of neILHR0∕PLH≈2.5±0.2×1019(A∕W∕m2). We have simulated the LH current drive in these discharges using the combined ray tracing/three-dimensional (r,v⊥,v∥) Fokker–Planck code GENRAY-CQL3D (R. W. Harvey and M. McCoy, in Proceedings of the IAEA Technical Committee Meeting on Simulation and Modeling of Thermonuclear Plasmas, Montreal, Canada, 1992) and found similar current drive efficiencies. The simulated profiles of current density from CQL3D, including both ohmic plus LH drive have been found to be in good agreement with the measured current density from a motional Stark effect diagnostic. Measurements of nonthermal x-ray emission confirm the presence of a significant fast electron population and the three-dimensional (r,v⊥,v∥) electron distribution function from CQL3D has been used in a synthetic diagnostic code to simulate the measured hard x-ray data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".