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Record W4372333587 · doi:10.1107/s1600577523003399

Soft X-ray spectro-ptychography of boron nitride nanobamboos, carbon nanotubes and permalloy nanorods

2023· article· en· W4372333587 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

VenueJournal of Synchrotron Radiation · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsMcMaster UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework ProgrammeMcMaster University
KeywordsPtychographyMaterials scienceBoron nitrideOpticsNanorodCarbon nanotubePermalloyHigh-resolution transmission electron microscopyDiffractionNanotechnologyPhysicsMagnetic field

Abstract

fetched live from OpenAlex

Spectro-ptychography offers improved spatial resolution and additional phase spectral information relative to that provided by scanning transmission X-ray microscopes. However, carrying out ptychography at the lower range of soft X-ray energies (e.g. below 200 eV to 600 eV) on samples with weakly scattering signals can be challenging. Here, results of soft X-ray spectro-ptychography at energies as low as 180 eV are presented, and its capabilities are illustrated with results from permalloy nanorods (Fe 2p), carbon nanotubes (C 1s) and boron nitride bamboo nanostructures (B 1s, N 1s). The optimization of low-energy X-ray spectro-ptychography is described and important challenges associated with measurement approaches, reconstruction algorithms and their effects on the reconstructed images are discussed. A method for evaluating the increase in radiation dose when using overlapping sampling is presented.

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 score0.076
Threshold uncertainty score0.741

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 head0.006
GPT teacher head0.253
Teacher spread0.248 · 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