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Record W2153413223 · doi:10.1017/s1431927610013504

Imaging, Core-Loss, and Low-Loss Electron-Energy-Loss Spectroscopy Mapping in Aberration-Corrected STEM

2010· article· en· W2153413223 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

VenueMicroscopy and Microanalysis · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsInstitut National de la Recherche ScientifiqueMcMaster University
Fundersnot available
KeywordsElectron energy loss spectroscopyCore (optical fiber)SpectroscopyMaterials scienceElectronOpticsPhysicsNuclear physicsAstronomy

Abstract

fetched live from OpenAlex

High-angle annular dark-field and annular bright-field imaging experiments were carried out on an aberration-corrected transmission electron microscope. These techniques have been demonstrated on thin films of complex oxides Ba3.25La0.75Ti3O12 and on LaB6. The results show good agreement between theory and experiments, and for the case of LaB6 they demonstrate the detection of contrast from the B atoms in the annular bright-field images. Elemental mapping with electron-energy-loss spectroscopy has been used to deduce the distribution of Cr and Fe in a thin film of the complex oxide Bi2(Fe1/2Cr3/2)O6 at the unit cell level and the changes in the near-edge structure within the inequivalent regions in the crystalline unit cell. Energy-filtered images in the low-loss region of the energy-loss spectrum show contrast and resolution consistent with the modulation of the signals from elastic scattering. High-resolution contrast, mediated by phonon scattering, is observed for interband transitions. The limitations in terms of detection and signal are discussed.

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 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 score0.027
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 head0.004
GPT teacher head0.270
Teacher spread0.266 · 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