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Record W4283262967 · doi:10.1515/joc-2021-0213

RETRACTED ARTICLE: Signal propagation parameters estimation through designed multi layer fibre with higher dominant modes using OptiFibre simulation

2022· article· en· W4283262967 on OpenAlexaff
Ahmed Nabih Zaki Rashed, Sk Hasane Ahammad, Malek G. Daher, Vishal Sorathiya, Abrar Siddique, Sayed Asaduzzaman, Hasin Rehana, Nitul Dutta, Shobhit K. Patel, Vincent Omollo Nyangaresi, Rayhan Habib Jibon, Anas Ibrahim

Post-publication record

OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.

Bibliographic record

VenueJournal of Optical Communications · 2022
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsModal dispersionModalDispersion (optics)Layer (electronics)SIGNAL (programming language)WavelengthOpticsMaterials scienceSubwavelength-diameter optical fibreMode (computer interface)AcousticsField (mathematics)Optical fiberPhysicsComputer scienceMathematicsDispersion-shifted fiberComposite materialFiber optic sensor

Abstract

fetched live from OpenAlex

Abstract The aim and scope of the paper is to simulate the signal propagation parameters estimation through designed multi-layer fibre with higher dominant modes by using OptiFibre simulation software. The multi-layer fibre profile has a length of 1000 m is designed and clarified with six layers. RI difference profile variations are clarified with radial distance variations. Modal/group index, group delay, dispersion, mode field diameter and total fibre losses are demonstrated with the fibre wavelength variations. All the dominant mode field distribution for multi-layer fibre are simulated and demonstrated. The other modes for designed multi-layer fibre with the theoretical fibre cutoff values for the different modes based the designed multi-layer fibre are analyzed and clarified clearly in details.

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 categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.082
GPT teacher head0.309
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.

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

Citations33
Published2022
Admission routes1
Has abstractyes

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