MétaCan
Menu
Back to cohort
Record W2028396154 · doi:10.1364/jocn.3.000797

Impact of Backreflections on Single-Fiber Bidirectional Transmission in WDM-PONs

2011· article· en· W2028396154 on OpenAlex
Shiyu Gao, Hanwu Hu, Hanan Anis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Optical Communications and Networking · 2011
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOptical line terminationPassive optical networkWavelength-division multiplexingRelative intensity noiseBeat (acoustics)OpticsMultiplexingLaser linewidthComputer scienceWavelengthElectronic engineeringPhysicsTelecommunicationsLaserEngineeringSemiconductor laser theory

Abstract

fetched live from OpenAlex

We analyze the system impairment due to beat noises between backreflections and the upstream signal in bidirectional single-fiber wavelength-division-multiplexing passive optical networks (WDM-PONs). The relative intensity noise (RIN), the power penalty caused by the beat noises and the optimum optical network unit (ONU) gain that minimizes this penalty are investigated. In addition to the transmission line loss (TLL), we find that these parameters are also dependent on the linewidth of the seed light, the chirp effect at the ONU and the receiver bandwidth. Different types of laser sources at the optical line terminal (OLT) and various wavelength-independent ONU configurations are intensively investigated to explore those dependencies. It is also found that the systems with remodulation configurations are more tolerant to the backreflections.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.341

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 integrity0.0000.001
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 head0.081
GPT teacher head0.296
Teacher spread0.214 · 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