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Record W2113377212 · doi:10.1039/c4cp04599h

Spin manipulation with magnetic semiconductor barriers

2014· article· en· W2113377212 on OpenAlexaff
Guo‐Xing Miao, Jagadeesh S. Moodera

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
FundersNational Science Foundation
KeywordsSemiconductorSpin (aerodynamics)Condensed matter physicsMagnetic semiconductorMaterials scienceNanotechnologyPhysicsOptoelectronics

Abstract

fetched live from OpenAlex

Magnetic semiconductors are a class of materials with special spin-filtering capabilities with magnetically tunable energy gaps. Many of these materials also possess another intrinsic property: indirect exchange interaction between the localized magnetic moments and the adjacent free electrons, which manifests as an extremely large effective magnetic field applying only on the spin degrees of freedom of the free electrons. Novel device concepts can be created by taking advantage of these properties. We discuss in the article the basic principles of these phenomena, and potential ways of applying them in constructing spintronic devices.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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.

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

Citations51
Published2014
Admission routes1
Has abstractyes

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