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Record W2969321523 · doi:10.1109/mcom.2019.1800851

Full Duplex DOCSIS: Opportunities and Challenges

2019· article· en· W2969321523 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.

Bibliographic record

VenueIEEE Communications Magazine · 2019
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPHYComputer scienceTelecommunicationsEconomic shortageComputer networkBandwidth (computing)EnablingCable modemWirelessPhysical layerGovernment (linguistics)

Abstract

fetched live from OpenAlex

The recently released full duplex extensions to the DOCSIS 3.1 standard (FDX DOCSIS) promise to greatly alleviate the shortage of upstream bandwidth that has plagued HFC networks since inception. However, there are a number of technical and implementation challenges in both the MAC and PHY layers of FDX DOCSIS that must be overcome in order for the standard to live up to its potential as a major enabler of next-generation services. Due to the relatively small and insular nature of the DOCSIS community, these challenges may not attract attention in the academic community commensurate with their importance. This article presents a high-level overview of FDX DOCSIS technology and describes some key technical challenges related to FDX DOCSIS which, if resolved appropriately, could provide significant value to the industry and society in general.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
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 head0.086
GPT teacher head0.260
Teacher spread0.174 · 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