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Record W3194230277 · doi:10.1364/oe.433435

Effect of retrace error on stitching coherent scanning interferometry measurements of freeform optics

2021· article· en· W3194230277 on OpenAlexaff
Hossein Shahinian, Clark Hovis, C. J. Evans

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsMicrosemi (Canada)
FundersUniversity of North Carolina at CharlotteNational Science Foundation
KeywordsImage stitchingOpticsInterferometryFizeau interferometerCoherence (philosophical gambling strategy)Measurement uncertaintyPhysicsMetrologyAperture (computer memory)Observational errorAstronomical interferometerMathematicsAcoustics

Abstract

fetched live from OpenAlex

We report on the effect of retrace error during measurement of freeform optics using a commercial coherence scanning interferometer (CSI), and its in-built stitching capabilities. It is shown that measuring segments of freeform optics under non-null conditions, results in artifacts on the measured zone, similar to the Seidel aberrations. An experimental approach is used to quantify the induced aberrations based on the local slopes of the surface. Simulation of surfaces containing different order aberrations is shown to have a significant effect on the measurement data. A correction method is proposed that uses experimental measurements to determine the required correction based on local slope and position in the aperture. These corrections reduce the measurement difference from a comparison measurement using a Fizeau interferometer.

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)0.001
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
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 head0.058
GPT teacher head0.316
Teacher spread0.258 · 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
GenreEmpirical

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

Citations29
Published2021
Admission routes1
Has abstractyes

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