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Record W2995284662 · doi:10.1109/cwit.2019.8929916

A Bounded-Noise Model for Nondispersive Optical Fiber

2019· article· en· W2995284662 on OpenAlexaff
Reza Rafie Borujeny, Frank R. Kschischang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBounded functionNoise (video)Computer scienceOptical fiberChannel (broadcasting)FiberNonlinear systemElectronic engineeringTelecommunicationsMathematicsPhysicsEngineeringMathematical analysisMaterials scienceArtificial intelligence

Abstract

fetched live from OpenAlex

A bounded-noise model for the nondispersive optical fiber channel is introduced. The new model is based on the so-called split-step model and is meant to facilitate understanding of capacity limitations caused by nonlinear signal-noise interactions in optical fiber. Some characteristics of the noise balls pertaining to this new model are discussed and, accordingly, upper and lower bounds on the zero-error capacity of this channel are found.

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 categoriesInsufficient payload (model declined to judge)
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 score0.379
Threshold uncertainty score1.000

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)0.0000.001

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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.

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

Citations1
Published2019
Admission routes1
Has abstractyes

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