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Record W3124160021 · doi:10.1109/glocom.1988.26081

Precision time-transfer in transport networks using digital crossconnect systems

2003· article· en· W3124160021 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsAlberta Energy
FundersGovernment of Alberta
KeywordsJitterComputer scienceSynchronization (alternating current)Time transferTransfer functionExploitTransfer (computing)Real-time computingComputer networkElectrical engineeringTelecommunicationsParallel computingGlobal Positioning SystemEngineering

Abstract

fetched live from OpenAlex

The authors describe a technique for precise synchronization of the time-of-delay clocks in networks of digital cross-connect systems (DCS), intended to enhance the performance of reconfigurable transport networks. The method is specifically devised to exploit the fine time resolution of the carrier signals to which a DCS has direct access. The resulting scheme is a master-slave, multisite, implicitly-delay-compensated, nonhierarchical time-transfer method with a theoretical precision of one bit time at the carrier rate. A worst-case estimate of delay asymmetry (including jitter effects) suggests that time-transfer error of under one microsecond should be obtainable. The method is most easily supported by an n/n space-switching DCS which has equal delay on all paths through its core and has a bridging connection feature. A circuit module for DCS hardware support of the time-transfer function is outlined.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.619

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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