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Record W4390331397 · doi:10.1109/mcom.2023.10375690

Optical Communications and Networks

2023· article· en· W4390331397 on OpenAlexaff
Mathieu Chagnon, Cedric F. Lam, Itsuro Morita

Bibliographic record

VenueIEEE Communications Magazine · 2023
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceComputer networkOptical Transport NetworkTelecommunicationsOptical communicationOptical performance monitoringClos network10G-PONKey (lock)Optical wirelessMultiwavelength optical networkingOptical cross-connectPassive optical networkOptical networkingWirelessElectronic engineeringOptical fiberWavelength-division multiplexingComputer securityOptoelectronicsFiber optic splitterEngineeringMaterials science

Abstract

fetched live from OpenAlex

In the last issue of the Optical Communications and Networks Series in 2023, we have selected six fascinating articles reporting on recent advances in optical communications and networking. They address “Digital Twins” for optical networks, Clos network for large scale ali-optical switching, novel failure localization framework for optical transport networks, quantum key distribution (QKD) networks enhanced by the paradigm of Information-Centric Networking (ICN), optical performance monitoring using artificial neural network and advanced optical detectors for high-speed optical wireless communication.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.036
GPT teacher head0.274
Teacher spread0.238 · 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
Published2023
Admission routes1
Has abstractyes

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