MétaCan
Menu
Back to cohort
Record W2971998295 · doi:10.1088/1367-2630/ab4386

Two-axis cavity optomechanical torque characterization of magnetic microstructures

2019· article· en· W2971998295 on OpenAlexafffund

Bibliographic record

VenueNew Journal of Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsNational Institute for NanotechnologyUniversity of AlbertaUniversity of Calgary
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsTorqueMagnetic momentTorsion (gastropod)AnisotropyMagnetic fieldCharacterization (materials science)Magnetic anisotropyPerpendicular

Abstract

fetched live from OpenAlex

Abstract Significant new functionality is reported for torsion mechanical tools aimed at full magnetic characterizations of both spin statics and dynamics in micro- and nanostructures. Specifically, two orthogonal torque directions are monitored and the results co-analyzed to separate magnetic moment and magnetic susceptibility contributions to torque, as is desired for characterization of anisotropic three-dimensional structures. The approach is demonstrated through application to shape and microstructural disorder-induced magnetic anisotropies in lithographically patterned permalloy, and will have utility for the determination of important magnetic thin-film and multilayer properties including interface anisotropy and exchange bias. The results reflect remarkable sensitivity of the out-of-plane magnetic torque to the nature of small edge domains perpendicular to the applied field direction, and also contain tantalizing indications of direct coupling to spin dynamics at the frequency of the mechanics.

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 categoriesInsufficient payload (model declined to judge)
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 score0.083
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)0.0010.000

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 head0.006
GPT teacher head0.240
Teacher spread0.233 · 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

Citations11
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueNew Journal of PhysicsSame topicMechanical and Optical ResonatorsFrench-language works237,207