SUPPORTING DISTRIBUTED AUTONOMOUS INFORMATION SERVICES USING COORDINATION
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 large quantity and often questionable quality of available information in the information age provides a shaky foundation for decision making by individuals and organizations alike. This has created a tremendous demand for information services which can access, filter, process and present information on an as-needed basis. However, two factors complicate the design of such information services, namely the distributed and the autonomous nature of data sources. This paper reports on the design and implementation of a generic architecture for supporting information services, which meets the above challenge. The architecture adopts concepts from conceptual modeling to offer a transparent description of the information sources' setting and uses active databases techniques to offer a declarative, event-based language for defining coordination rules for integrating distributed information services. Accordingly, the proposed architecture supports two of the most prominent utilities of information services, namely the pre-designed flow of operations and the reactive provision of information. In addition to describing the architecture and illustrating its features with an example, the paper presents a prototype implementation and reports on some experimental performance results.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.027 |
| 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