Design of a 2-D magnetizer with the consideration of the z-component of the magnetic field
Bibliographic record
Abstract
A magnetizer design methodology that takes into account systematic errors such as the variation in flux density (B), and the z-component of the magnetic field (Hz), is proposed. The effect of the sample diameter and the effective length of the yoke, i.e. yoke depth on Hz are analysed. Experimental results at 1.5 T and 60 Hz showed a reduction of 81 %, 72 % and 30 % by a large magnetizer, shielding and reducing the yoke depth from 80 mm to 10 mm, respectively. This was in comparison to an unshielded compact magnetizer. Hz is also dependent on magnetic loading. Furthermore, at 2 T and 60 Hz, magnetic contributions dominated Hz such that the effectiveness of shielding and reducing the yoke depth decreased to 27 % and 4 %, respectively. To achieve these very high flux densities, the magnetizers were designed to be compact (sample diameter of ≤ 100 mm and narrow airgaps of ≤ 2 mm). This reduction in size increases the leakage field above and below the sample to the same level of magnitude as the applied field, which affects the measurement of the magnetic field (H). Two H-coil sizes with a sensitivity difference of 60 % are used to show that the measured H is independent of the coil size, but depends on the leakage field. Their measured core loss difference under pulsating and rotating fields was about 6 %.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".