Product metamodel based on the coupling of the extended design matrix X -DSM and SysML formalism
Bibliographic record
Abstract
This paper proposes an approach to semantic modeling of products based on an extended version of the DSM Design Structure Matrix (DSM), called here, X-DSM (extended DSM) and on the SysML formalism. This metamodel is intended to take into account the structural characteristics of the product and its behavior along the life cycle, from the design phase to its end of life. For that, first, we proposed 4 types of X-DSM matrices that are used to represent the components, design parameters, activities and the associated project's stakeholders. And then, we use SysML language diagrams to represent the behavioral views of the product at different stages of its lifecycle. The proposed metamodel complies with the SysML formalism including both the 7 UML4SysML views and 2 additional views aimed to the care of Specifications and Parametric settings. These last two views are key factors for modeling products with multiple configurations. In the second part of the article, we propose implementation architecture to exploit the functionalities of such a metamodel in collaborative design.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".