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Record W2105768841 · doi:10.5381/jot.2004.3.8.a3

Generic Pipelined Multi-Agents Architecture for Multimedia Multimodal Software Environment.

2004· article· en· W2105768841 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Object Technology · 2004
Typearticle
Languageen
FieldComputer Science
TopicSpeech and dialogue systems
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceFlexibility (engineering)ArchitectureInterface (matter)Computer architectureAgent architectureReference architectureIntelligent agentDistributed computingSoftware architectureEmbedded systemHuman–computer interactionSoftwareArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

Multimodal human-computer interaction needs intelligent architectures in order to enhance the flexibility and naturelness of the user interface. These architectures have the ability to manage several multithreaded input signals from different input media in order to perform their fusion into intelligent commands. In this paper, a generic comprehensive agent-based architecture for multimodal engine fusion is proposed. The architecture is sketched in term of its relevant components. Each element is modeled using timed colored Petri networks. The generic components of the engine fusion are then included in a pipelined based-agent global architecture for which the architectural quality attributes are outlined.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.723
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0020.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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