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Record W4283805062 · doi:10.1103/physrevb.106.l041102

Acoustic phonon dispersion of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>α</mml:mi><mml:mtext>−</mml:mtext><mml:msub><mml:mi mathvariant="normal">RuCl</mml:mi><mml:mn>3</mml:mn></mml:msub></mml:math>

2022· article· lv· W4283805062 on OpenAlexafffund
Blair W. Lebert, Subin Kim, Danil Prishchenko, Alexander A. Tsirlin, Ayman Said, Ahmet Alatas, Young‐June Kim

Bibliographic record

VenuePhysical review. B./Physical review. B · 2022
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsUniversity of Toronto
FundersArgonne National LaboratoryNatural Sciences and Engineering Research Council of CanadaRussian Science FoundationDeutsche ForschungsgemeinschaftOntario Innovation Trust
KeywordsPhononOrder (exchange)Dispersion (optics)PhysicsSpace (punctuation)Condensed matter physicsCrystallographyMachine learningChemistryComputer scienceOptics

Abstract

fetched live from OpenAlex

Acoustic phonons have recently been posited as playing an integral role in explaining the half-quantized thermal Hall effect in $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{RuCl}}_{3}$. Therefore, we present much needed inelastic x-ray scattering measurements of its acoustic phonon dispersion, along with calculations using the frozen-phonon method. We also discuss a temperature study which conclusively shows a first-order structural transition to a non-$C2/m$ space group at low temperature. Together these results are an important backbone for future theoretical and experimental studies of $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{RuCl}}_{3}$.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.015
GPT teacher head0.276
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2022
Admission routes2
Has abstractyes

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