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Record W4400487993 · doi:10.1109/msmc.2024.3377181

E-CARGO/RBC Research Guide: A Road Map for Researchers

2024· article· en· W4400487993 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Systems Man and Cybernetics Magazine · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsNipissing University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsRoad mapAeronauticsTransport engineeringComputer scienceMarine engineeringEngineeringGeographyCartography

Abstract

fetched live from OpenAlex

In addition to outlining the key components of the Environments – Classes, Agents, Roles, Groups, and Objects (E-CARGO) model and Role-Based Collaboration (RBC) methodology, this article aims to serve as a comprehensive research guide for scholars and researchers embarking on investigations within their research fields. By offering persuasive and illustrative arguments, the authors furnish valuable and pragmatic guidelines, equipping potential researchers with insights on selecting pertinent topics, crafting compelling scenarios, engaging in effective modeling practices, and designing rigorous experiments. The elucidation of these fundamental steps not only facilitates a clearer understanding of the intricate aspects of E-CARGO and RBC but also provides a road map for researchers to navigate the intricacies of conducting solid and insightful research within these frameworks.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.599
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.354
GPT teacher head0.520
Teacher spread0.166 · 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