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Record W2992334038 · doi:10.1103/physrevlett.96.037206

Static Magnetic Order in Metallic<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi mathvariant="normal">K</mml:mi><mml:mn>0.49</mml:mn></mml:msub><mml:msub><mml:mi>CoO</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:math>

2006· article· lv· W2992334038 on OpenAlexafffund
Jun Sugiyama, Hiroshi Nozaki, Yutaka Ikedo, Kazuhiko Mukai, J. H. Brewer, Eduardo J. Ansaldo, G.D. Morris, Daniel Andreica, A. Amato, T. Fujii, A. Asamitsu

Bibliographic record

VenuePhysical Review Letters · 2006
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsUniversity of British ColumbiaTRIUMF
FundersNatural Sciences and Engineering Research Council of CanadaTRIUMF
KeywordsParamagnetismValence (chemistry)Condensed matter physicsPhysicsOrder (exchange)MuonCrystallographyMaterials scienceChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

By means of muon-spin spectroscopy, we have found that K0.49CoO2 crystals undergo successive magnetic transitions from a high-T paramagnetic state to a magnetic ordered state below 60 K and then to a second ordered state below 16 K, even though K0.49CoO2 is metallic at least down to 4 K. An isotropic magnetic behavior and wide internal-field distributions suggest the formation of a commensurate helical spin density wave (SDW) state below 16 K, while a linear SDW state is likely to exist above 16 K. It was also found that exhibits a further transition at 150 K presumably due to a change in the spin state of the Co ions. Since the dependence of the internal-field below 60 K was similar to that for Na0.5CoO2, this suggests that magnetic order is more strongly affected by the Co valence than by the interlayer distance or interaction and/or the charge ordering.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0790.006

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 head0.242
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

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

Citations24
Published2006
Admission routes2
Has abstractyes

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