S&D Pattern Deployment at Organizational Level: A Prototype for Remote Healthcare System
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 analysis of security incidents and frauds has shown that several vulnerabilities of IT systems are due to loopholes in the policies and procedures adopted by organizations as well as in their structure. Organizations have thus to address security and dependability issues by analyzing their organizational setting. In this paper, we present a methodology to support the deployment of Security & Dependability patterns according to their position in the Enterprise Architecture and the underlying system infrastructures. The methodology discriminates the pattern deployment process between recommendations and guidelines. Recommendations concretize the deployment with refined software and/or hardware related patterns, whereas guidelines specify the organizational patterns in terms of the system-to-be, proposing human-resource and/or policy solutions. To make the discussion more concrete, we illustrate the framework with a case study on an emergency scenario within a remote healthcare system.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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