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Record W2957600311 · doi:10.4018/ijossp.2019040101

NorJADE

2019· article· en· W2957600311 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

VenueInternational Journal of Open Source Software and Processes · 2019
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsComputer scienceJADE (particle detector)Modular designSoftware engineeringProcess (computing)OntologyDomain (mathematical analysis)ExtensibilityNormativeSimple (philosophy)Open sourceSoftwareProgramming language

Abstract

fetched live from OpenAlex

Normative multi-agent systems are multi-agent systems where agents are governed by norms. This recent research domain is now in full expansion. Despite the progress made in this area, various challenges remain the subject of research studies. In particular, there is a need for innovative solutions to support the implementation of this kind of multi-agent systems in order to improve the development process and consequently to simplify the developers' task. In the literature, most proposed works in this area are either closely related to specific problems or require complicated theoretical frameworks. In this article, a new framework baptized NorJADE is proposed to support the implementation of normative multi-agent systems. The proposed framework is open source, simple, modular and extensible. It is based on the popular open source JADE platform and uses the two well-known software technologies: ontology and aspect-oriented programming. The framework and the associated tool are illustrated using a concrete case study.

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 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 score0.880
Threshold uncertainty score0.629

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 communication0.0010.002
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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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