Real-space investigation of short-range magnetic correlations in fluoride pyrochlores <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>NaCaCo</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">F</mml:mi><mml:mn>7</mml:mn></mml:msub></mml:mrow></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>NaSrCo</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">F</mml:mi><mml:mn>7</mml:mn></mml:msub></mml:mrow></mml:math> with magnetic pair distribution function analysis
Bibliographic record
Abstract
In geometrically frustrated magnets the crystal lattice prevents competing magnetic interactions from being simultaneously satisfied. Consequently these materials often possess fascinating magnetic properties such as unusual short-range magnetic correlations. However, studying short-range magnetic structure has historically been a notoriously difficult experimental task. Here, Frandsen $e\phantom{\rule{0}{0ex}}t$ $a\phantom{\rule{0}{0ex}}l$. apply a new experimental technique---magnetic pair distribution function (mPDF) analysis---to uncover the local magnetic structure and temperature dependence of recently-discovered frustrated magnets NaMCo${}^{2}$F${}^{7}$ (M=Ca,Sr). The results further establish these materials as an important new class of geometrically frustrated magnets with observable frustration effects at unusually high temperatures (~200 K), while also opening the door for a plethora of future studies of frustrated magnets using the mPDF method.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".