Data analysis methods and applications of the eddy current diagnostic system in the Keda Torus eXperiment device
Bibliographic record
Abstract
Abstract Since the establishment of the eddy current diagnostic system within the Keda Torus eXperiment (KTX) device, it has unveiled many applications. Recent developments have introduced innovative data analysis techniques alongside compelling experimental results, underscoring the necessity for a comprehensive summary of the system's data analysis approaches and broad applications. Notable features of the system encompass exceptional precision, the ability to encompass shell currents on the entirety of the closed boundary, vector detection of shell currents, and measurement of diverse physical quantities. In terms of data analysis methodologies, meticulous scrutiny of the null field region is conducted, and we reveal a distinctive characteristic within the complex shell current signals, namely the asymmetry of the amplitudes of ± n Fourier coefficients. Moreover, the Hodge decomposition emerges as a pivotal technique, allowing for the distinctive separation of shell currents into three orthogonal components based on their distinct spatial topological properties. With regard to practical applications, an in-depth examination of the vector potential and magnetic helicity flux densities are presented in detail, further highlighting the far-reaching utility of the system's capabilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".