Design and Development of a Blockchain-Based System for Private Data Management
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 concept of blockchain was introduced as the Bitcoin cryptocurrency in a 2008 whitepaper by the mysterious Satoshi Nakamoto. Blockchain has applications in many domains, such as healthcare, the Internet of Things (IoT), and data management. Data management is defined as obtaining, processing, safeguarding, and storing information about an organization to aid with making better business decisions for the firm. The collected information is often shared across organizations without the consent of the individuals who provided the information. As a result, the information must be protected from unauthorized access or exploitation. Therefore, organizations must ensure that their systems are transparent to build user confidence. This paper introduces the architectural design and development of a blockchain-based system for private data management, discusses the proof-of-concept prototype using Hyperledger Fabric, and presents evaluation results of the proposed system using Hyperledger Caliper. The proposed solution can be used in any application domain where managing the privacy of user data is important, such as in health care systems.
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 | 0.001 | 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