Random Fields and the Partially Paramagnetic State of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mrow><mml:mi mathvariant="normal">C</mml:mi><mml:mi mathvariant="normal">s</mml:mi><mml:mi mathvariant="normal">C</mml:mi><mml:mi mathvariant="normal">o</mml:mi></mml:mrow><mml:mn>0.83</mml:mn></mml:msub><mml:msub><mml:mrow><mml:mi mathvariant="normal">M</mml:mi><mml:mi mathvariant="normal">g</mml:mi></mml:mrow><mml:mn>0.17</mml:mn></mml:msub><mml:msub><mml:mrow><mml:mi mathvariant="normal">B</mml:mi><mml:mi mathvariant="normal">r</mml:mi></mml:mrow><mml:mn>3</mml:mn></mml:msub></mml:math>: Critical Scattering Study
Bibliographic record
Abstract
We have performed measurements of the critical neutron scattering on ${\mathrm{C}\mathrm{s}\mathrm{C}\mathrm{o}}_{0.83}{\mathrm{M}\mathrm{g}}_{0.17}{\mathrm{B}\mathrm{r}}_{3}$, a dilute stacked triangular lattice (STL) Ising antiferromagnet (AF). A two component line shape associated with the critical fluctuations appears at a temperature coincident with ${T}_{N1}$ observed in pure ${\mathrm{C}\mathrm{s}\mathrm{C}\mathrm{o}\mathrm{B}\mathrm{r}}_{3}$. Such scattering is indicative of fluctuations in prototypical random field Ising model (RFIM) systems. The random field domain state arises in this case due to geometrical frustration within the STL Ising AF, which gives rise to a three sublattice N\'eel state, in which one sublattice is disordered. Magnetic vacancies nucleate AF domains in which the vacancies reside on the disordered sublattice thereby generating a RFIM state in the absence of an applied magnetic field.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.070 | 0.012 |
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".