Antonio Vallecillo
Bibliographic record
Abstract
As we present this issue of the Journal of Software and Systems Modeling (SoSyM), we take a moment to acknowledge and celebrate the remarkable contributions of Professor Antonio Vallecillo.After decades of dedication to the field, Antonio is now retiring, leaving behind an impressive amount of results in software and systems modeling.He has been a cornerstone of our journal, serving as an editor almost from the very beginning of SoSyM's 25 year journey.He was always helpful as editor, advisor, and friend.His expertise, vision, and continuous commitment have significantly shaped not only the special section presented in this issue, but also the broader research community.Antonio has played a long lasting and pivotal role in advancing the journal's mission, ensuring the highest standards of quality in published research, and fostering a strong sense of collaboration among researchers.His influence extends well beyond SoSyM; he has been a driving force in the development of modeling techniques, particularly in the domains of cyber-physical systems (CPSs), uncertainty B Benoit Combemale
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.033 | 0.020 |
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".