MétaCan
Menu
Back to cohort

A Polarization Maintaining Cladding Light Stripper with Ultra-Low Backscattering, Based on 20/400-μm Double Clad Fiber

2025· article· en· W4413461017 on OpenAlexfundno aff
Jihwan Kim, Ju Han Lee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsnot available
FundersInstitute for Information and Communications Technology PromotionInformation Technology Research CentreMinistry of Science and ICT, South Korea
KeywordsCladding (metalworking)Materials scienceOptical fiberPolarization (electrochemistry)OptoelectronicsOpticsComposite materialPhysicsChemistry

Abstract

fetched live from OpenAlex

High-power optical fiber laser systems are currently widely used in various applications such as materials processing, medicine, and defense [1]. High-power optical fiber laser technologies employ large mode area (LMA), double clad fibers (DCFs) to increase output power by using a cladding pumping scheme [2]. For the successful implementation of LMA DCF-based high power fiber lasers one of the key components is the cladding light stripper (CLS). It is well-known that a non-negligible amount of residual pump power always exists at the output end of a gain medium based on rare-earth ion-doped LMA DCF after the launched pump beam was used to induce stimulated emission. The residual pump beam together with undesired signal beam within the inner cladding of a LMA DCF is known to degrade output beam quality and potentially damage fiber splicing points. In implementing CLSs, one critical issue is the backward scattering of cladding light since it can induce fiber heating and burning [3]. It was also reported that conventional CLS designs based on randomly roughened surface structures or periodically V-grooved structures are vulnerable to the residual pump backscattering [4], [5]

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 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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.698
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicPhotonic Crystal and Fiber OpticsFrench-language works237,207