Bibliographic record
Abstract
There are many different constraints when assigning agents to roles within a group. One such constraint is role coupling.. It is a complex problem that cannot be solved without appropriate modelling tools. The Role-Based Collaboration (RBC) and its Environments - Classes, Agents, Roles, Groups, and Objects (E-CARGO) model is such a tool. This paper proposes a solution to the role assignment problem in consideration of role coupling through the application of this tool. The problem can be described as a Group Multi-Role Assignment with Coupled Roles (GMRACR). It is considered as a multi-objective non-linear optimization problem. Useful solutions are implemented by using a Linear Programming (LP) solver, i.e., the IBM ILOG CPLEX optimization Platform (CPLEX). Experiments are then conducted to verify the proposed solutions. Contributions of this paper include formalization of the GMRACR problem. This provides the foundation for finding an objetive solution and advances the state of the art on the subject of assignment. The proposed solutions provide a solid foundation for decision making in dealing with similar issues.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".