Metamodelling with formal semantics with application to access control specification
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
The visual aspect of metamodelling languages is an efficient lever to deal with the complexity of specifying systems. In many application domains, these systems are generally characterized by the sensitivity and criticality of their contents, hence precision and formalism are essential goals. This paper considers the domain of access control specification languages and proposes a metamodelling paradigm with capabilities for specifying both semantics and structuring elements. We describe how to specify semantics of domain specific systems at the metamodel and model levels. The paradigm defines reusable rules allowing mapping the models, including their semantics, to first order logic programs. It represents a methodical approach to elaborate domain specific languages endowed with visual aspects and means of reasoning on formal specifications. The paradigm is applicable to a wide range of systems. We show in this paper its application in the area of decision systems.
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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 it