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Record W2106549466 · doi:10.1109/tsmca.2006.883176

Discovering and Managing Access to Private Services in Collaborative Sessions

2006· article· en· W2106549466 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 Transactions on Systems Man and Cybernetics - Part A Systems and Humans · 2006
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsDalhousie UniversityOntario Tech University
Fundersnot available
KeywordsSession (web analytics)Service discoveryComputer scienceSession Initiation ProtocolProtocol (science)ConversationService (business)Task (project management)Private networkThe InternetWorld Wide WebComputer networkWeb serviceServerEngineering

Abstract

fetched live from OpenAlex

An approach that integrates service discovery with the Internet Engineering Task Force session initiation protocol to support service discovery of private services across a collaborative session is presented. Embedding the service discovery protocol within a session protocol facilitates the discovery of private services in a safe and controlled manner. Access to services is managed by defining local scopes that are shared among participants in the collaborative session. The fundamentals of the approach are presented using a simple two-party scenario and further extended by describing the approach using both central and peer-to-peer collaborative scenarios. Finally, the feasibility of the approach is demonstrated through a proof-of-concept demonstration of the sharing of Bluetooth services located in a private wireless personal area network across a telephone conversation

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), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
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 communication0.0010.001
Open science0.0000.000
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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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