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Record W2957440557 · doi:10.1088/1361-6404/ab2fef

Use of interference colours to distinguish between fast and slow axes of a quarter wave plate

2019· article· en· W2957440557 on OpenAlexaboutno aff
Archana Shah, Pallavi Ghalsasi

Bibliographic record

VenueEuropean Journal of Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Measurement and Metrology Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsInterference (communication)Quarter (Canadian coin)WaveplateOpticsTelecommunicationsChannel (broadcasting)History

Abstract

fetched live from OpenAlex

Abstract A quarter wave plate is commonly used to generate circularly and elliptically polarized light owing to its birefringent property. The orientation of its fast and slow axes with respect to linearly polarized light decides the resultant polarization. Often, low-priced wave plates do not come with their fast and slow axes marked. Users are supposed to conduct a test based on colour changes as seen while tilting the quarter wave plate and assigning the respective axes. Although this procedure is routinely advised, the physics behind the typically observed colours is seldom discussed in the literature. The present article is structured as a tutorial to understand the origin of observed interference colours while a quarter wave plate is tilted about its fast or slow axes. The explanation is given on the basis of the Michel Levy interference colour chart. At the same time, the tutorial is intended to introduce new researchers from multidisciplinary fields like physics, geology, mineralogy and chemistry to basics pertaining to birefringence in a comprehensive way as they are not taught in disciplinary college/university curricula otherwise.

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)0.001
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.040
GPT teacher head0.233
Teacher spread0.192 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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