MétaCan
Menu
Back to cohort
Record W2172291758 · doi:10.1109/istas.2008.4559765

An H.323 Broadband Virtual Camera for supporting asynchronous visual communication in large groups

2008· article· en· W2172291758 on OpenAlexaff
Bruno Emond, David Scobie, Matthew Allen, Michael Postma, William J. McIver

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSession (web analytics)Computer scienceAsynchronous communicationVideoconferencingProtocol (science)MultimediaComputer networkInterface (matter)BroadbandSession Initiation ProtocolBroadband networksThe InternetPoint (geometry)TeleconferencePoint-to-pointOperating systemServerTelecommunicationsWorld Wide Web

Abstract

fetched live from OpenAlex

BVCAM is a video recording service based on the H.323 protocol for videoconferencing on IP networks. BVCAM allows remote recording of H.323 sessions either as a point-to-point session or as an endpoint in a multipoint session. All recordings are controlled through a web interface. The initial conception of BVCAM was to complement synchronous communication in large group meetings so that distributed problem-solving teams could keep in touch with what is discussed remotely.

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)0.001
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 score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.005

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 head0.029
GPT teacher head0.372
Teacher spread0.343 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same topicMultimedia Communication and TechnologyFrench-language works237,207