Quantum critical behavior in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>Ce</mml:mi><mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:msub><mml:mi>Fe</mml:mi><mml:mrow><mml:mn>0.76</mml:mn></mml:mrow></mml:msub><mml:msub><mml:mi>Ru</mml:mi><mml:mrow><mml:mn>0.24</mml:mn></mml:mrow></mml:msub><mml:mo>)</mml:mo></mml:mrow><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>Ge</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math>
Bibliographic record
Abstract
Systems with embedded magnetic ions that exhibit a competition between magnetic order and disorder down to absolute zero can display unusual low-temperature behaviors of the resistivity, susceptibility, and specific heat. Moreover, the dynamic response of such a system can display hyperscaling behavior in which the relaxation back to equilibrium when an amount of energy $E$ is given to the system at temperature $T$ only depends on the ratio $E/T$. $\mathrm{Ce}{({\mathrm{Fe}}_{0.755}{\mathrm{Ru}}_{0.245})}_{2}{\mathrm{Ge}}_{2}$ is a system that displays these behaviors. We show that these complex behaviors are rooted in a fragmentation of the magnetic lattice upon cooling caused by a distribution of local Kondo screening temperatures, and that the hyperscaling behavior can be attributed to the flipping of the total magnetic moment of magnetic clusters that spontaneously form and order upon cooling. We present our arguments based on the review of two-decades worth of neutron scattering and transport data on this system, augmented with new polarized and unpolarized neutron scattering experiments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.005 | 0.010 |
| Meta-epidemiology (broad) | 0.002 | 0.013 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.011 | 0.009 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.882 | 0.017 |
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; both teacher heads agree on what is shown here.
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".