Viewing Project Collaborators WhoWork on Interrelated Requirements
Bibliographic record
Abstract
Project collaborators in a software development project need to stay aware not only of changes to requirements and other artifacts, but also of each other's current work. The set of team members working on a requirement is dynamic, and team members who were not assigned to the requirement in the plan may be involved. If this requirement changes, those team members who are dependent on that requirement must be notified quickly before they do outdated work. However, project plans often do not provide an easy method of listing all of the emergent team members who should be notified of changes to a requirement. We propose a requirements-dependency diagram that displays interdependent requirements and team members who are assigned to these interdependent requirements. The visualization highlights prominent collaborators, lists each collaborator and each requirement only once, marks emergent collaborators, and is simple and clutter-free. By viewing this diagram, collaborators will know who to contact to notify others of changes to requirements, and can contact experts working on interrelated requirements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".