Low-energy spin excitations in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mi>Mn</mml:mi><mml:mrow><mml:mn>3</mml:mn><mml:mo>×</mml:mo><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>molecular nanomagnets
Bibliographic record
Abstract
NMR and $\ensuremath{\mu}\mathrm{SR}$ relaxation measurements in the ${\mathrm{Mn}}_{9}{({\mathrm{C}}_{19}{\mathrm{H}}_{15}{\mathrm{N}}_{9}{\mathrm{O}}_{2})}_{6}{({\mathrm{ClO}}_{4})}_{6}.18{\mathrm{H}}_{2}\mathrm{O}({\mathrm{Mn}}_{3\ifmmode\times\else\texttimes\fi{}3})$ molecular grid are presented. The temperature dependence of the relaxation rates can be conveniently described by a single correlation time for the spin fluctuations at temperatures of the order of the exchange coupling among ${\mathrm{Mn}}^{2+}$ ions. The inverse of the correlation time is observed to reach the MHz range at low temperature and its temperature dependence can be justified on the basis of a theoretical model where the electron spin fluctuations are driven by spin-phonon coupling. Finally, it is pointed out that the magnetic field dependence of the $\ensuremath{\mu}\mathrm{SR}$ relaxation rate allows one to derive the Zeeman splitting of the low-energy spin levels.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.240 | 0.046 |
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".