Providing support for process model enaction in the Metaview metasystem
Bibliographic record
Abstract
Process modeling is a means of formally defining many aspects of the software development process through the use of models. Partial automation of a process model can help to improve the software process. Menial or tedious tasks, such as collecting metrics, no longer have to be the responsibility of the developer. Coordination of effort can also be enhanced through automation. Automation can be achieved through the development of a process modeling support environment and the appropriate CASE tools. This is one of the major goals of the Metaview project, which involves the design and development of a metasystem to generate such an environment. A key requirement for this type of support environment is to use an active database. Active databases can react through an action to events, such as changes to a particular data item, thereby giving them the flexibility needed for process modeling. The paper presents an execution model for the support of process model enaction in the Metaview system. The execution model is intended to support a wide variety of process models and process modeling languages. The model is based upon the event rule model used in active databases.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".