HCX: A Distributed OSGi Based Web Interaction System for Sharing Health Records in the Cloud
Bibliographic record
Abstract
WITH the maturity of Web Services and Enterprise Service Oriented Architectures (SOA), new delivery and Web interaction models are now demonstrating how services can be traded outside traditional ownership and provisioning boundaries. The value of SOA comes from having an architecture that readily accommodates change. The more your business changes, the more SOA pays for itself. However, the initial build-out of SOA, prior to business change or service sharing, is cost-ineffective. By incorporating cloud computing in SOA, the time to value is shortened because you leverage `other people's work' as well as saving on infrastructure cost by leveraging on demand cloud based infrastructure services. This article outlines a distributed Web interactive system for sharing health records on the cloud using distributed OSGi services and consumers, called HCX (Health Cloud eXchange). This system allows for different health record and related healthcare services to be dynamically discovered and interactively used by client programs running within a federated private cloud. A basic prototype is presented as proof of concept along with a description to the steps and processes involved in setting up the underlying infrastructure. Finally some future directions for using this infrastructure are illustrated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".