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Record W3205271236 · doi:10.1364/ol.446159

Single-shot wide-field topography measurement using spectrally multiplexed reflection intensity holography via space-domain Kramers–Kronig relations

2022· article· en· W3205271236 on OpenAlexaff
Chungha Lee, YoonSeok Baek, Hervé Hugonnet, YongKeun Park

Bibliographic record

VenueOptics Letters · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDigital Holography and Microscopy
Canadian institutionsKootenay Association for Science & Technology
FundersInstitute for Information and Communications Technology PromotionNational Research Foundation of Korea
KeywordsOpticsHolographyMetrologyMultiplexingPtychographyPhysicsReflection (computer programming)Spatial frequencyPhase retrievalImage resolutionMaterials scienceFourier transformDiffractionComputer science

Abstract

fetched live from OpenAlex

Surface topology measurements of micro- or nanostructures are essential for both scientific and industrial applications. However, high-throughput measurements remain challenging in surface metrology. We present single-shot full-field surface topography measurement using Kramers-Kronig holographic imaging and spectral multiplexing. Three different intensity images at different incident angles were simultaneously measured with three different colors, from which a quantitative phase image was retrieved using spatial Kramers-Kronig relations. A high-resolution topographic image of the sample was then reconstructed using synthetic aperture holography. Various patterned structures at the nanometer scale were measured and cross-validated using atomic force microscopy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.032
GPT teacher head0.246
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations35
Published2022
Admission routes1
Has abstractyes

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