MétaCan
Menu
Back to cohort
Record W4402919154 · doi:10.1063/5.0220393

A phase-correction approach for enhancing mid-infrared electro-optic sampling in highly nonlinear and dispersive birefringent crystals

2024· article· en· W4402919154 on OpenAlexafffund
B. N. Carnio, Mingyuan Zhang, Oussama Moutanabbir, A. Y. Elezzabi

Bibliographic record

VenueApplied Physics Letters · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOptical and Acousto-Optic Technologies
Canadian institutionsPolytechnique MontréalUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBirefringenceInfraredMaterials scienceOpticsNonlinear opticsPhase (matter)Nonlinear opticalNonlinear systemOptical materialsSampling (signal processing)Electro-opticsOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Spectral content in the mid-infrared range is recorded experimentally via a (110)-cut ZnGeP2 electro-optic sampling crystal followed by a ZnGeP2 phase-correction crystal, with the two crystals oriented to exhibit offsetting birefringences on the electric fields associated with the electro-optic sampling process. An enhancement of >13 times is observed in the recorded electro-optic signal (when comparing the electro-optic signals obtained in the presence and absence of the phase-correction crystal). A transfer function embodying this phase-corrected electro-optic sampling approach is derived and subsequently implemented to identify unique spectral features observed in the experimentally recorded electro-optic spectra.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.246
Teacher spread0.235 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueApplied Physics LettersSame topicOptical and Acousto-Optic TechnologiesFrench-language works237,207