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Record W2106679639 · doi:10.1109/cts.2006.73

XML Agents Technology for Building Collaborative Applications

2006· article· en· W2106679639 on OpenAlexaff
Weichang Du, Hui Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsComputer scienceXMLSOAPWorld Wide WebEfficient XML InterchangeWeb serviceXML frameworkXML SignatureStreaming XML

Abstract

fetched live from OpenAlex

This paper describes an XML based agents technology for building web services based collaborative applications. The technology consists of XML Agents (XAs), XML Agent Hosts, and XML based Agent Communication Language (XACL). The XML based XAs and XACL messages are neutral to particular agent systems and programming languages. The XML Agent Hosts are implemented using Web Services technology. The hosts provide services to XML agents and agent communications that are represented as Web service requests, and provide runtime environments for performing visiting agents’ behaviors that are implemented in multiple programming languages. Collaborative applications can be built using two types of agent collaborations, agent communications through XACL and agent visiting. XAs reside in different hosts can collaborate each other be exchanging XACL messages. Also XAs can "meet" face to face in a host supported by XAs’ mobility. Mobile XAs support more dynamic collaborations by their dynamic behaviors with different collaboration partners in different hosts.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.006
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.007

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 head0.008
GPT teacher head0.254
Teacher spread0.247 · 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 designSimulation or modeling
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

Citations3
Published2006
Admission routes1
Has abstractyes

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