Construction of an Hα diagnostic system and its application to determine neutral hydrogen densities on the Keda Torus eXperiment*
Bibliographic record
Abstract
A 10-channel H α diagnostic system has been designed with the rapid response rate of 300 kHz, spatial resolution of about 40 mm, and overlap between adjacent channels of about 3%, and it has been implemented successfully on Keda Torus eXperiment (KTX), a newly constructed, reversed field pinch (RFP) experimental device at the University of Science and Technology of China (USTC). This diagnostic system is a very important tool for the initial KTX operations. It is compact, with an aperture slit replacing the traditional optical lens system. A flexural interference filter is designed to prevent the center wavelength from shifting too much as the increase of angle from vertical incidence. To eliminate the stray light, the interior of the system is covered with the black aluminum foil having a very high absorptivity. Using the H α emission data, together with the profiles of electron temperature and density obtained from the Langmuir probe, the neutral density profiles have been calculated for KTX plasmas. The rapid response rate and good spatial resolution of this H α diagnostic system will be beneficial for many studies in RFP plasma physics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".