Probing nanoscale behavior of magnetic materials with soft X-ray spectromicroscopy
Bibliographic record
Abstract
The Nanotechnology Reviews (NTREV) journal aims at all aspects of nano-science and nano-engineering as well as emerging innovative topics of all areas of engineering science at the nanoscale , nano-energy , nano-biomaterials , and nano-composites . The journal emphasizes interdisciplinary and multi-functional research and linkage between nanotechnology and composites technology . Non-nano papers with potential significant future contributions to nano-research may be welcomed on a case by case basis. These topics include: bio-inspired/soft materials , 3D/4D printing , molecular dynamics/multi-scale modeling , imaging , batteries , graphene/carbon nano tubes , nano-mechanics , and many others. Check out the latest table of contents at a glance with easy access to most cited and most downloaded Nanotechnology Reviews’ papers of 2020 and 2021 ! Table of contents 2020 Table of contents 2021
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".