Strengthening of Reentrant Pinning by Collective Interactions in the Peak Effect
Bibliographic record
Abstract
Since it was first observed about 40 years ago [A. B. Pippard, Proc. R. Soc. A 216, 547 (1953)10.1098/rspa.1953.0040], the peak effect has been the subject of extensive research mainly impelled by the desire to determine its exact mechanisms. Despite these efforts, a consensus on this question has yet to be reached. Experimentally, the peak effect indicates a transition from a depinned vortex phase to a reentrant pinning phase at a high magnetic field. To study the effects of intrinsic pinning on the peak effect, we consider FexNi1-xZr2 superconducting metallic glasses in which the vortex pinning force varies depending on the Fe content and in which a huge peak effect is seen. The results show that the peak effect broadens with decreasing pinning force. Typically, pinning is increased by pinning centers, but here we show that reentrant pinning is due to the strengthening of interactions and collective effects (while decreasing pinning strength).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".