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Record W4247820400 · doi:10.32920/ryerson.14639475

The Other Mobile TV: ATSC MDTV Broadcasting In Canada

2021· preprint· en· W4247820400 on OpenAlexaffabout
Steven J. May, Catherine A. Middleton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBroadcasting (networking)TelecommunicationsDigital broadcastingService (business)Commercial broadcastingTerrestrial televisionMobile serviceComputer scienceDigital televisionAdvertisingBusinessPublic broadcastingMultimediaComputer securityMarketing

Abstract

fetched live from OpenAlex

This commentary describes an approach for delivering television content to mobile phones in Canada using over-the-air broadcast signals. Over-the-air television broadcasting to mobile phones is available to our American neighbours but has not been implemented in Canada. We report on a test of mobile TV services, demonstrating access to U.S. signals from Canada. While it is technically feasible to deliver over-the-air mobile broadcasting in Canada, it is likely that vertical integration in the broadcasting and communications sectors is creating barriers to the development of this service. The commentary concludes with some thoughts on how mobile digital television services could be developed for Canadian viewers.

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.493

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0140.004
Scholarly communication0.0070.002
Open science0.0020.001
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0160.002

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 head0.036
GPT teacher head0.325
Teacher spread0.289 · 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
Published2021
Admission routes2
Has abstractyes

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Same topicMultimedia Communication and TechnologyFrench-language works237,207