Bibliographic record
Abstract
Electron temperatures have been measured in a 1 kJ Mather-type dense plasma focus\ndevice (UofS-I DPF) with a hollow copper anode at the University of Saskatchewan (UofS)\nPlasma Physics Lab (PPL). The UofS-I DPF device is powered by a 5 F capacitor bank\ncharged up to 20 kV with an optimum operating pressure of 100 - 200 mTorr argon gas. The\nfeatures of the plasma dynamics in the UofS-I DPF device have been studied by analyzing\nsignals of the discharge current, the anode voltage, the intensities of electron and ion beams,\nand the soft x-ray (SXR) and hard x-ray (HXR) radiations. The peak times of signals have\nbeen compared with the pinch time. A negatively-biased BPX-65 Si-PIN photodiode array\nhas been used to measure SXR emissions from the UofS-I DPF. The double- lter technique\nand the ratio method have been used to determine the electron temperature based on the\nmeasured SXR intensities. An electron temperature of 5.7 0.7 keV has been obtained\nfor the argon plasma. Moreover, linear correlations of the current dip, the peaks of the\nelectron beam and the SXR and HXR emissions with the peak of the anode voltage have\nbeen observed. Linear correlations of the same signals with the electron temperature have\nalso been observed.\nThe Lee model code has been used to determine the optimum capacitor bank voltage\nand operating pressure for the UofS-I DPF. The Lee code has also been used for tting the\nexperimental current waveform to the computed waveform in order to obtain the mass and\ncurrent factors. These factors allow the computations of the radial positions and the speeds\nof the focusing plasma.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".