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Record W4283819573 · doi:10.1103/revmodphys.94.045004

Ultrafast electron diffraction: Visualizing dynamic states of matter

2022· preprint· en· W4283819573 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueReviews of Modern Physics · 2022
Typepreprint
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaTsinghua UniversityU.S. Department of EnergyNational Science Foundation
KeywordsUltrafast electron diffractionUltrashort pulseState of matterPhysicsElectronElectron diffractionNanotechnologyEngineering physicsLaserDiffractionMaterials scienceOpticsNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Understanding the structure and function of both energy and matter is a fundamental goal in science. Various spatiotemporal probes have been developed from electromagnetic waves spanning the entire range of the spectrum to neutrons and charged particles such as electrons. With the development of highly controlled, shorter electron bunches, retrieving dynamic structural information from solid-state and gas-phase samples is now possible at timescales that resolve atomic motion and length scales that resolve atomic positions in even the lightest elements. In this review advances in the generation, manipulation, and characterization of ultrashort electron beams are described.

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)0.001
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 score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.343
Teacher spread0.321 · 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