Reversible and quasireversible information in first-order reversal curve diagrams
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Bibliographic record
Abstract
Two methods for extracting information from first-order reversal curves (FORCs) obtained on low coercivity samples are presented. The proportion of reversibility as a function of applied field can be extracted by calculating the ratio of the initial slope of each FORC to the susceptibility on the major hysteresis loop upper branch at the same field. This gives us the part of the reversal process, a process occurring with zero coercivity, that is, where H=Hr, during the magnetization reversal. In order to be able to see the nonperturbed trace coming from the irreversible processes with a small coercivity compared to the FORC domain, some points have to be added in the H<Hr area in a way that minimizes the discontinuities near H=Hr. This is done by using two functions characterizing the behavior of the magnetization on the H=Hr axis (“extrapolated FORCs”). These methods were used to characterize a CoFeB nanowire array with the applied field perpendicular to the nanowire axis.
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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 | 0.000 |
| 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) | 0.000 | 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 it