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Record W2790474494 · doi:10.1017/s1551929500053785

Energy-Filtered Electron Holography

2005· article· en· W2790474494 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 Today · 2005
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsElectronPhysicsScatteringLattice (music)HolographyCoherence (philosophical gambling strategy)Atomic physicsSpatial coherenceComputational physicsOpticsNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract When electrons pass through a material, they can pass through without losing energy such as elastically scattered electrons or they can lose or gain energy by inelastically scattering with the material's electrons. The elastically scattered electrons have been used in the simulations of lattice images, which are used to help determine the atomic structure of materials. Inelastically scattered electrons were ignored in the simulations because it was believed that they did not have the required coherence to interfere with themselves and they contributed only to the background intensity. Recently though, a great deal of interest has been generated in knowing whether the inelastically scattered electrons can also contribute to the lattice images in order to help explain the Stobbs factor [1], where the contrast in the lattice images is often three or more times less than the theory predicts. The Stobbs factor makes it difficult, if not impossible, to establish quantitative values to high-resolution lattice images.

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), Insufficient 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 score0.129
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 science0.0010.000
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 head0.007
GPT teacher head0.273
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