Heat Transport as a Probe of Electron Scattering by Spin Fluctuations: The Case of Antiferromagnetic<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>CeRhIn</mml:mi><mml:mn>5</mml:mn></mml:msub></mml:math>
Bibliographic record
Abstract
Heat and charge conduction were measured in the heavy-fermion metal ${\mathrm{CeRhIn}}_{5}$, an antiferromagnet with ${T}_{N}=3.8\text{ }\text{ }\mathrm{K}$. The thermal resistivity is found to be proportional to the magnetic entropy, revealing that spin fluctuations are as effective in scattering electrons as they are in disordering local moments. The electrical resistivity, governed by a ${\mathbf{q}}^{2}$ weighting of fluctuations, increases monotonically with temperature. In contrast, the difference between thermal and electrical resistivities, characterized by a ${\ensuremath{\omega}}^{2}$ weighting, peaks sharply at ${T}_{N}$ and eventually goes to zero at a temperature ${T}^{\ensuremath{\star}}\ensuremath{\simeq}8\text{ }\text{ }\mathrm{K}$. ${T}^{\ensuremath{\star}}$ thus emerges as a measure of the characteristic energy of magnetic fluctuations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".