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Record W4415589743 · doi:10.1364/radit.2025.rm1d.1

High-Energy X-Ray Multipixel Ghost Imaging at 20 µm Resolution: A Scalable Approach for NDT and Biomedical Applications

2025· article· W4415589743 on OpenAlexaff
O. Sefi, A. Ben Yehuda, Y. Klein, Z. Sobol, S. Bloch, Hila Schwartz, Eliahu Cohen, S. Shwartz

Bibliographic record

Venuenot available
Typearticle
Language
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGhost imagingNondestructive testingMedical imagingScalabilityImaging techniqueHigh resolutionImage resolution

Abstract

fetched live from OpenAlex

We demonstrate high-energy x-ray multipixel ghost imaging achieving 20 µm resolution over 0.9×1 cm 2 with only 1000 realizations. The method opens new avenues for high-resolution, scalable, noninvasive NDT and medical imaging of subsurface and internal structures.

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.

How this classification was reachedexpand

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.223
Teacher spread0.217 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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