A flexible metamodelling approach for healthcare systems
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
Abstract. Model driven software engineering (MDSE) is an emerging methodology for software development, targeting productivity, flexibility and reliability of systems; metamodelling is at the core of most MDSE approaches. Due to their complexity and plethora of requirements placed upon them, healthcare systems so far have not been adequately modeled; as a result the software developed for them suffers from high develop-ment costs and lack of flexibility, and its reliability is at risk. Here we propose a metamodelling approach that captures the complexity of these systems by using a metamodelling hierarchy, built from five metamod-els, one each for user access modelling, health process modelling, process monitoring, user interface modelling and modelling of the data sources. These metamodels are coordinated with morphisms. Such a hierarchy allows us to adequately reflect the behavior and complexities of systems and how they interact with different stakeholders. We give details of some of the metamodels and present some suggestions for some different interfaces intended for two different users: the clinicians and the patients. 1
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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