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Record W2395769360

A Multi-Agent-Based Approach for Autonomic Data Exchange Processes.

2014· article· en· W2395769360 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

VenueSoftware Engineering and Knowledge Engineering · 2014
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer scienceAutonomic computingDependabilityData exchangeSchema matchingDistributed computingSchema (genetic algorithms)CorrectnessData integrationSoftware engineeringData miningDatabaseCloud computingInformation retrievalOperating systemProgramming language
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we present a prototype for our solution called Data Exchange Autonomic Manager (DEAM) [1] which has as main goal to turn Data Exchange processes into selfmanaged systems. We believe that providing data exchange processes with self-healing autonomic capability is a promising approach toward reliable self-managed and resilient data exchange processes. We describe the high level architecture of DEAM prototype which leverages well established techniques and technologies for Autonomic Computing (Multi-Agent Systems) and Schema Matching (Automatic Schema Matching and Mapping). Keywords-data exchange; autonomic computing; self-managed systems; dependability; fault tolerance; sufficient correctness; schema matching; schema mapping; mapping adaptation; multiagent systems; agent based modelling and simulation

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.182
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 communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.230
Teacher spread0.209 · 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