Jiles–Atherton model used in the magnetization process study for the composite magnetoelectric materials based on cobalt ferrite and barium titanate
Bibliographic record
Abstract
This paper presents the use of the Jiles–Atherton model in fitting the major magnetization curves for two classes of composite magnetoelectric materials. These materials are: (BaTiO3)x(CoFe2O4)1–x and (BaTiO3)x(CoMn0.2Fe1.8O4)1–x, with x = 0.8, 0.6, and 0.4. The model’s parameters result from finding the regression curves and give information about the micromagnetic state of the material. The dependencies of the model’s parameters on the ratio of the two phases’ concentrations have been analyzed. The values of the parameters for the two classes of materials have been compared, and the influence of Mn on the magnetic properties has been analyzed. Also presented here are the regression curves for a set of first order reversal curves using the same algorithm as the major magnetization curves. The dependence of the model’s parameters on the reversal field has been analyzed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".