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
Having fast and dependable access to the most relevant information available is of the utmost importance in a competitive information-oriented society. Ensuring transparent and dependable access to a large number of heterogeneous, ill-structured and often distributed data and information sources is a complex problem with many different facets. Over time a large variety of very different approaches have been developed. Among the many competing approaches, information agents seem to be particularly well suited to the challenges of the information cyberspace due to their highly adaptive and distributed problem solving. Only information agents seem capable to offer the much needed user centric access to the myriads of data and information sources accessible via the web. But just like other agents, they require significant computational resources making it difficult to build scalable systems.This paper has two aims. First it is an attempt to draw attention to the scalability challenges in developing systems consisting of large numbers of information agents. Second, it presents a CORBA based framework called DICE for building information agents and reports about its use in developing real world systems based on information agents.
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 | 0.000 | 0.001 |
| 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