An Adaptive Context-Aware and Event-Based Framework Design Model
Why this work is in the frame
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Bibliographic record
Abstract
Context-aware and proactive technologies have been continuously used over the past years to improve user interaction in areas such as searching and information retrieval, health care and mobile computing. Although there have been significant advances in context-aware systems, there is still a lack of approaches that model and implement context-aware proactive applications involving the combination of context and distributed events. In this paper we address these issues by defining a context-aware event model, a new context-aware publish subscribe scheme and a distributed event-based framework. Our proposed event model is implemented as a context-aware distributed eventbased framework that provides the necessary infrastructure to publish and deliver events based on a component's context. In summary, we are able to leverage context as part of our event model and bring behaviour context-aware adaptation to publication and subscription of events.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 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