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Record W2920694809 · doi:10.1117/12.2506629

Holographic camera for non-contact measurement of nanoscale surface heights

2019· article· en· W2920694809 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

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDigital Holography and Microscopy
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsOpticsHolographyImage resolutionInterferometryMaterials scienceHolographic interferometryInterference (communication)Resolution (logic)PhysicsComputer visionArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

We report on the development of a holographic camera capable of measuring nanometer-scale surface features. The system is based on a modified off-axis Mach-Zehnder interferometer and was optimized to provide high-quality interference patterns. Fast imaging was implemented with a time-gated intensified CCD camera directly facing the surface of the object. By increasing the intensifier gain, holographic images with good contrast could be captured within 1 ns. We tested the ability of the camera to measure nanometer-scale height differences using a patterned USAF target. The depth resolution of the camera was estimated to be better than 10 nm. We also found that both the object-CCD distance and the angle between the object and reference beams had significant impact on the quality of the reconstructed surface profiles. Potential applications of the camera include measurement of tissue surface displacements for non-contact photoacoustic imaging.

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 score0.400
Threshold uncertainty score0.397

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 head0.010
GPT teacher head0.227
Teacher spread0.218 · 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

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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