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Record W2748886598 · doi:10.1142/s2010135x17500291

Structural and magnetic properties of La0.7Sr0.3MnO<sub>3</sub> ferromagnetic thin film grown on PMN-PT by sol–gel method

2017· article· en· W2748886598 on OpenAlexaff
Jing Zhang, Peng Shi, Mingmin Zhu, Ming Liu, Wei Ren, Zuo‐Guang Ye

Bibliographic record

VenueJournal of Advanced Dielectrics · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic and transport properties of perovskites and related materials
Canadian institutionsSimon Fraser University
FundersHigher Education Discipline Innovation ProjectInternational Joint Laboratory for MicroNano Manufacturing and Measurement Technologies
KeywordsFerromagnetismThin filmMaterials scienceMagnetoresistanceCondensed matter physicsHysteresisEpitaxyDiffractionSol-gelCrystallographyPhase (matter)Atomic force microscopyAnalytical Chemistry (journal)NanotechnologyPhysicsOpticsQuantum mechanicsChemistryMagnetic field

Abstract

fetched live from OpenAlex

We report the preparation of epitaxial La[Formula: see text]Sr[Formula: see text]MnO3 thin films grown on (001)-oriented 0.72Pb(Mg[Formula: see text]Nb[Formula: see text]O3-0.28PbTiO3 substrates by the sol–gel technique. The phase structure, magnetic properties and magnetoresistance of the samples are investigated by using high solution X-ray diffraction, atomic force microscopy, physical property measurement system, respectively. The La[Formula: see text]Sr[Formula: see text]MnO3 thin films display a well-defined hysteresis loop and typical ferromagnetism behavior at lower temperature. High magnetoresistance at 5[Formula: see text]T of 42% appears at 227[Formula: see text]K for La[Formula: see text]Sr[Formula: see text]MnO3 thin film.

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 score0.003

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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