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Record W2161033934 · doi:10.1364/ol.36.000526

Dynamic phase evaluation in sparse-sampled temporal speckle pattern sequence

2011· article· en· W2161033934 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

VenueOptics Letters · 2011
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSpeckle patternPhase retrievalComputer scienceElectronic speckle pattern interferometrySpeckle noiseInterferometrySpeckle imagingOpticsSampling (signal processing)WaveletArtificial intelligenceFourier transformPhase (matter)Computer visionMathematicsPhysics

Abstract

fetched live from OpenAlex

The rapid progress of modern manufacturing technology has posed stringent requirements for inspecting techniques for vibration characterization and dynamic testing. Because of its simplicity, accuracy, and whole-field character, speckle interferometry has served as one of the major techniques for dynamic measurement, where normally a dense-sampled temporal speckle sequence is captured for phase retrieval using Fourier or wavelet transforms. In this Letter, a method is proposed for phase evaluation of sparse-sampled speckle patterns when the sampling rate is lower than two points per temporal cycle. Dynamic experiments using a high-speed camera demonstrated the effectiveness of the proposed method for complicated wrapped phase retrieval in electronic/digital speckle pattern interferometry.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.152
GPT teacher head0.332
Teacher spread0.180 · 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