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Record W2096201141 · doi:10.1109/ccece.2005.1557175

Current and future developments related to the sonet

2006· article· en· W2096201141 on OpenAlexaff
A. Ateeq, Love Kumar, Myong-Lyol Song, Tianying Ji

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSynchronous optical networkingWavelength-division multiplexingComputer networkBandwidth (computing)Computer scienceOptical mesh networkTelecommunicationsDigital cross connect systemOptical Carrier transmission ratesMultiplexingOptical fiberWavelengthMaterials scienceWirelessOptoelectronicsWireless mesh networkRadio over fiber

Abstract

fetched live from OpenAlex

The insatiable desire for increased bandwidth led to the development and deployment of optical technology. However the potential of this technology has not been fully exploited. Currently, SONET sets the standard for optical communications with bit rates of up to 9.8 Gbps per wavelength channel. Although wavelength division multiplexing (WDM) has been deployed, the number of wavelength channels per fiber is relatively small at the current time. Dense WDM that better utilizes the fiber capability further boosts the SONET capacity, along with the next generation bit rate of 40 Gbps. Current research and development in this area is utilizing this high bandwidth availability for future integrated data transmissions, such as packets over SONET, broadcast TV, video on demand, and video conferencing. These applications in turn induces fundamental impact on SONET itself, which leads to a new generation of technologies evolving from SONET, such as MPLS.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0300.007

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 head0.004
GPT teacher head0.205
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2006
Admission routes1
Has abstractyes

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