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Standardizing Web TV: Adapting ATSC 3.0 for Use on any IP Network

2024· article· en· W4401164161 on OpenAlexaff
Jordan Melzer, Natan Melzer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTelecommunications and Broadcasting Technologies
Canadian institutionsYork UniversityTelus (Canada)
Fundersnot available
KeywordsComputer scienceDigital televisionComputer networkThe InternetWorld Wide WebTelecommunications

Abstract

fetched live from OpenAlex

The ATSC 3.0 family of standards and the associated NEXTGEN TV brand define a new technology generation for broadcast television. As a hybrid TV standard, ATSC 3.0 allows for both video and HTML5 content and delivery via broadband as well as over-the-air broadcast. Presently, though ATSC 3.0 allows for video and applications to be delivered over any Internet Protocol network, it only allows them to be discovered via an over-the-air broadcast. Here we propose simple changes to ATSC 3.0’s A/331 Signaling, Delivery, Synchronization, and Error Protection specification to allow for discovery of channels automatically on any IP connection via well-known multicast or via HTTPS aided by DNS Service Discovery on domains that are provided by an ISP or user or are well-known. These changes would allow an ATSC 3.0 TV to connect not just to content discovered via broadcast signaling but also to ATSC 3.0 conformant channels and applications discovered on the local network; provided by a cellular network, ISP or IPTV provider; or available publicly on the WWW. Completing the broadband capability of ATSC 3.0 would allow users on compliant TVs to channel surf to live content, streaming services, local devices and web apps, keeping more users on the native TV UI. Making ATSC 3.0 signaling more broadly accessible positions ATSC 3.0 more clearly as a universal runtime for both applications and video, reducing the need within the industry for proprietary application platforms and hardware dongles.

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)0.007
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0050.006
Open science0.0040.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0070.009

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 head0.045
GPT teacher head0.261
Teacher spread0.217 · 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
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
Published2024
Admission routes1
Has abstractyes

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