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Record W3028132602 · doi:10.1134/s0030400x20080251

Super-Achromatic Quarter-Wave Phase Retarder for Visible, Near Infrared, and Short Wave Infrared Region Applications

2020· article· en· W3028132602 on OpenAlexaboutno aff
Nilanjan Mukhopadhyay, Arijit Saha, Kaushik Bhattacharya

Bibliographic record

VenueOptics and Spectroscopy · 2020
Typearticle
Languageen
FieldEngineering
TopicOptical Polarization and Ellipsometry
Canadian institutionsnot available
Fundersnot available
KeywordsAchromatic lensInfraredOpticsRetarderPhase (matter)Materials scienceQuarter (Canadian coin)Physics

Abstract

fetched live from OpenAlex

Abstract Phase retarders are essential components in optical system design as they can control the phase shifts associated with the vector components of incoming light waves and hence, decide the state of polarization. Different optical systems are designed to work at different wavelength spectrums. Most of these developments focus on the different wavelength regions between visible to infrared, of which the near infrared and short-wave infrared ranges are popular domains for defense and remote sensing applications. In this present communication, a super achromatic quarter-wave phase retarder consisting of four birefringent plates of different materials, i.e., KDP, crystalline quartz, ADP and ZnS has been proposed, to cover the visible, near infrared and short wave infrared regions from 400–2100 nm. As circularly polarized light is less affected by atmospheric conditions the use of an achromatic broadband quarter-wave phase retarder as proposed is quite useful. The proposed system shows acceptable performance over the intended range of wavelengths.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.251
Teacher spread0.228 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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