Computer Automated Multi-Paradigm Modeling: An Introduction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Modeling and simulation are quickly becoming the primary enablers for complex system design. They allow the representation of intricate knowledge at various levels of abstraction and allow automated analysis as well as synthesis. The heterogeneity of the design process, as much as of the system itself, however, requires a manifold of formalisms tailored to the specific task at hand. Efficient design approaches aim to combine different models of a system under study and maximally use the knowledge captured in them. Computer Automated Multi-Paradigm Modeling (CAMPaM) is the emerging field that addresses the issues involved and formulates a domain-independent framework along three dimensions: (1) multiple levels of abstraction, (2) multiformalism modeling, and (3) meta-modeling. This article presents an overview of the CAMPaM field and shows how transformations assume a central place. These transformation are, in turn, explicitly modeled themselves by graph grammars.
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.
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 | 0.001 |
| 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 it