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Record W1968130567 · doi:10.1002/pssr.200903032

Effects of correlated disorder on the magneto‐transport in colossal magnetoresistance manganites

2009· article· en· W1968130567 on OpenAlexaff
M. Egilmez, Z. Salman, K. H. Chow, J. Jung

Bibliographic record

Venuephysica status solidi (RRL) - Rapid Research Letters · 2009
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic and transport properties of perovskites and related materials
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsManganiteCondensed matter physicsMagnetoresistanceColossal magnetoresistanceElectrical resistivity and conductivityMaterials scienceAnnealing (glass)Metal–insulator transitionFerromagnetismPhysicsMagnetic fieldMetallurgy

Abstract

fetched live from OpenAlex

Abstract Monte‐Carlo simulations predict that a local correlated disorder is responsible for many of the novel transport and magnetic properties of colossal magnetoresistance (CMR) materials such as manganites. One important prediction of these models is that the resistivity at the metal–insulator transition (MIT) in manganites depends strongly on the correlated quenched disorder. However, experimental confirmation has been challenging since it is difficult to control the amount of disorder in these compounds. We carried out experiments on Sm 0.55 Sr 0.45 MnO 3 , a prototypical CMR manganite with a sharp MIT, whereby the oxygen‐related disorder is systematically enhanced by low temperature thermal activation. We observe dramatic changes in the temperature dependence of resistivity at the MIT as the amount of quenched disorder is increased, occurring in a manner that is in agreement with theoretical predictions. magnified image Temperature dependence of resistivity of Sm 0.55 Sr 0.45 MnO 3 for different annealing times at 350 °C in vacuum. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.162
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.255
Teacher spread0.241 · 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 teacher head, 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

Citations0
Published2009
Admission routes1
Has abstractyes

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