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Record W2165780875 · doi:10.1364/jocn.2.000001

Experimental Study of Burst-Mode Reception in a 1300 km Deployed Fiber Link

2009· article· en· W2165780875 on OpenAlex
Bhavin J. Shastri, Yousra Ben M’Sallem, Nicholas Zicha, Leslie A. Rusch, Sophie LaRochelle, David V. Plant

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Optical Communications and Networking · 2009
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversité LavalMcGill University
Fundersnot available
KeywordsBurst mode (computing)Link (geometry)Mode (computer interface)Computer scienceTelecommunicationsComputer networkOperating system

Abstract

fetched live from OpenAlex

We experimentally demonstrate burst-mode reception in a 1300 km fiber link that spans from Montreal to Quebec City and back, with a 1.25 Gb/s burst-mode receiver (BMRx). The receiver features automatic phase acquisition using a clock phase aligner (CPA) and provides instantaneous (0 preamble bit) phase acquisition with error-free operation [packet-loss ratio (PLR) <10−6 and bit error rate (BER) <10−10] for any phase step (±2π rad) between consecutive packets, while also supporting more than 1100 consecutive identical digits (CIDs). The CPA makes use of a phase picking algorithm and an oversampling semi-blind clock and data recovery circuit operated at 2× the bit rate. We also study the effect of channel impairments on the performance of BMRx at such distances. More specifically, we investigate the PLR performance of the system and quantify it as a function of the phase step between consecutive packets, received signal power, CID immunity, and BER, while assessing the trade-offs in preamble length, power penalty, and pattern correlator error resistance.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.388

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 head0.032
GPT teacher head0.301
Teacher spread0.269 · 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