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Record W4285484822 · doi:10.2478/candc-2021-0003

Design science research approach in studying e-negotiations: models, systems, experiments

2021· article· en· W4285484822 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

VenueControl and Cybernetics · 2021
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsLakehead University
Fundersnot available
KeywordsNegotiationFraming (construction)Perspective (graphical)Management scienceField (mathematics)Computer scienceDesign science researchSociologyEngineering ethicsKnowledge managementInformation systemEngineeringSocial scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Inspired and led by Dr. Gregory E. Kersten, a number of research projects have been conducted at the InterNeg Research Centre. This paper intends to acknowledge Dr. Kersten’s unique role as a pioneer in e-negotiation research, particularly in exploring and integrating various elements in e-negotiations. From the design science research perspective, this paper reviews a series of relevant research works in e-negotiation modeling, system design and development, and experimental studies. This provides an integrative view of interconnected elements in this field, and also helps framing the various studies into different aspects and stages of e-negotiation research. The paper then suggests several guidelines and directions for future design science research in e-negotiations.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.170
GPT teacher head0.339
Teacher spread0.169 · 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