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Record W2082904869 · doi:10.1063/1.4913875

Mechanism of sign crossover of the anisotropic magneto-resistance in La0.7−<i>x</i>Pr<i>x</i>Ca0.3MnO3 thin films

2015· article· en· W2082904869 on OpenAlexafffund
H. S. Alagoz, J. Desomberg, Maryam Taheri, F. S. Razavi, K. H. Chow, J. Jung

Bibliographic record

VenueApplied Physics Letters · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic and transport properties of perovskites and related materials
Canadian institutionsBrock UniversityUniversity of Alberta
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsCondensed matter physicsManganiteMaterials scienceMagnetizationAnisotropyThin filmMagnetic anisotropyElectrical resistivity and conductivityPerpendicularSign (mathematics)Film planeResistive touchscreenMagnetic fieldFerromagnetismOpticsNanotechnologyPhysics

Abstract

fetched live from OpenAlex

Magneto-resistive anisotropy (AMR) has been studied in 45 nm thick La0.7−xPrxCa0.3MnO3 (LPCMO) manganite films (with Pr doping x between 0 and 0.40) deposited on LaAlO3 (LAO) and SrTiO3 (STO) substrates. The AMR in compressively strained films undergoes a sign change from positive to negative at low temperatures, whereas its sign does not change in films subjected to tensile strain. Temperature dependence of magnetization in a magnetic field applied parallel and perpendicular to the (100)-plane of the films shows that at low temperatures strain-induced rotation of the easy-axis magnetization determines the sign of the AMR. At higher temperatures near the TMI the sign of the AMR is the same in both LPCMO/LAO and LPCMO/STO films, suggesting the dominating influence of percolative transport in the plane of these films at these temperatures.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.192
Teacher spread0.181 · 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

Citations21
Published2015
Admission routes2
Has abstractyes

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Same venueApplied Physics LettersSame topicMagnetic and transport properties of perovskites and related materialsFrench-language works237,207