Hi everyone,
Following up on our recent CDSS working group discussion regarding literature variable extraction, Minimum Viable Dataset (MVD) structuring, and risk stratification for operational flight monitoring (e.g., SANS / EVA alarm scoring):
I have prepared an architectural integration proposal detailing how **`MGSACore`** serves as the core processing engine to support these pipelines and prevent redundant codebase development.
### 
Core Resources & Citation
* **GitHub Repository:** [https://github.com/Montiel06/MGSACore\](GitHub - Montiel06/MGSACore: Enterprise LLM interpretability, sequence salience audit, and prompt optimization framework powered by LIT and Gemma open models. Developed by Vanguardia MGSA. · GitHub)
* **Persistent DOI (Zenodo):** [](MGSACore: LLM Interpretability, Attention Salience & Prompt Optimization Framework | Zenodo)
* **Full Technical Proposal (Google Doc):** [Technical Proposal: Integration of MGSACore into CDSS Ecosystem](https://docs.google.com/document/d/1N64t9s3F8XKQu7eC3Xl5QmE7lBNoUpQLWt3LtIK7XxA/edit?usp=drive_web)
* **Author Profiles:** [ORCID (0009-0007-5796-5881)](ORCID) | [LinkedIn](https://www.linkedin.com/in/vanessa-montiel-ruiz)
### 
Architectural Overview
```text
±----------------------------------------------------------------------+
| INPUT SOURCES |
| - Literature Extraction Matrix (27 papers) - Synthetic Cohorts |
| - Mission & Temporal Metadata - Surrogate Risk Proxies |
±----------------------------------------------------------------------+
|
v
±----------------------------------------------------------------------+
| MGSACore |
| [Ingestion & Validation] → [Normalization/Mapping] → [Rule/ML Engine]|
| - Unified Data Schema - Physical Correlations - Triage Logic|
±----------------------------------------------------------------------+
|
v
±----------------------------------------------------------------------+
| APPLICATION & DECISION |
| - Operational Early Alarms (Adaptive EVA Planning) |
| - CDSS Clinical Next-Step Actions & Triaging |
±----------------------------------
------------------------------------+
Key Alignment with Subgroup Tasks
Minimum Viable Dataset (MVD) & Data Modeling: MGSACore provides the base data models, validation classes, and JSON payload contracts to structure synthetic cohort generation.
Variable Dictionary: Normalization boundaries and variable types in the codebase can directly map to the plain-language scientific dictionary being assembled.
Surrogate Risk & Alarm Scoring: The inference interface is designed to compute rapid early-warning scores from non-invasive metrics (e.g., IOP, refractive shifts, physiological proxies) even when direct ocular imaging is constrained.
Feedback and suggestions on schema compatibility are welcome directly on the Google Doc or in this thread