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Record W2061796038 · doi:10.1126/science.1065300

Advances in Magnetic Microscopy

2001· article· en· W2061796038 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience · 2001
Typearticle
Languageen
FieldEngineering
TopicNear-Field Optical Microscopy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMagnetismMicroscopyNanotechnologyPaceCuriosityComputer scienceMaterials sciencePhysicsOpticsCondensed matter physicsPsychologyNeuroscience

Abstract

fetched live from OpenAlex

A remarkable number of methods for direct, real-space imaging in magnetic microscopy have been demonstrated over the past decade and a half, and the pace of development shows no sign of slowing. Our understanding of magnetism increases as each striking new image of surface and thin-film magnetization is obtained. The continued development of high-performance magnetic information technologies also requires detailed study of the magnetostatics and dynamics of microscopic magnetic structures. Both fundamental curiosity and practical interest now drive us toward innovations in magnetic microscopy for nanometer-length scale and femtosecond temporal resolutions, which are beyond the limits of traditional imaging techniques. This survey is intended to provide an overview of the motivations, accomplishments, and future prospects for this discipline.

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.

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 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 score0.213
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.251
Teacher spread0.247 · 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