Towards Modular Combination and Reuse of Languages with Perspectives
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
To describe the characteristics of a complex system, model-driven engineering (MDE) advocates the use of different modelling languages and multiple views. This allows the use of the most appropriate modelling language for expressing a specific system characteristic. However, maintaining the consistency between the views during the lifetime of the system is non-trivial. Moreover, languages can be added or removed from a multi-language system, which can be a daunting endeavour. We propose a framework for the specification and development of multi-language systems based on perspectives. A perspective groups different languages for a modelling purpose. A perspective defines composite actions for building a consistent multi-model view and then maintaining the relationships between different language elements. These actions are specified by re-exposing, combining, or redefining existing language actions offered by the languages the perspective reuses. Perspectives support a proactive and reactive approach for handling inconsistencies between different language elements.
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 | 0.000 |
| 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