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Evaluating Frequency Error Property of Wavefront of Large Optics by PSD Collapse

2007· article· en· W1968855027 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

VenueKey engineering materials · 2007
Typearticle
Languageen
FieldEngineering
TopicOptical Systems and Laser Technology
Canadian institutionsCanadian Association of Emergency Physicians
FundersUniversity of Electronic Science and Technology of China
KeywordsWavefrontSpectral densityOpticsPhysicsAdaptive opticsPhysical opticsPower (physics)Computer scienceTelecommunications

Abstract

fetched live from OpenAlex

Operation of two-dimensional Power Spectral Density (2-D PSD) of large optics wavefront is briefly described and PSD collapse is introduced to evaluate the intermediate frequency error property of wavefront. As PSD collapse is Radon transform projection of 2-D Power Spectral Density at any angle, all valid data of wavefront of optics are used in calculation of the PSD collapse and the features of 1-D PSD were inherited in PSD collapse. Although PSD collapse is as same as 1-D PSD in unit and behavior style, it is better for evaluating intermediate frequency error property of optics wavefront than 1-D PSD or 2-D PSD. As PSD collapse calculation uses all valid data of evaluated optics wave front and can be directly perceived through its profile, the PSD collapse may possibly be the standard evaluating method of PSD.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.631

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 communication0.0000.000
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 head0.016
GPT teacher head0.258
Teacher spread0.243 · 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