Foreword
Bibliographic record
Abstract
The purpose of this workshop is to study and advance the effective use of models in the engineering of software systems. In particular, we are interested in the exchange of experiences, challenges and promising technologies related to modeling. The goals of the software modeling community are to improve the productivity of software developers and to improve the quality of the resulting software products. Models are useful in all phases and activities surrounding software development and deployment. Thus, workshop topics range from requirements modeling, to runtime models, to models for assessing software quality, and to the pragmatics of how to manage large collections of models. This year, we received 23 submissions. Of these, the program committee accepted 11 papers for long presentations and 3 papers papers for shorter presentations, for an acceptance rate of 61%. These papers form the basis of workshop sessions, each of which starts with short presentations of 2-3 papers, followed by discussions of issues and research opportunities raised by the papers and by the session topic in general. The program also includes two keynotes, a panel discussion, and a poster/demo session.
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 | 0.000 | 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) | 0.000 | 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".