Multi-sensor and Information-Based Event Triggered Distributed Estimation
Why this work is in the frame
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Bibliographic record
Abstract
The paper is motivated by recent surge of interest in utilization of a large number of sensor nodes in cyber-physical systems (CPSs) and the critical importance of managing sensor's restricted resources. In this regard, we propose a multi-sensor and open-loop estimation algorithm with an information-based triggering mechanism. In the open-loop topology considered in this paper, each sensor transfers its measurements to the fusion centre (FC) only in occurrence of specific events (asynchronously). Events are identified using the information-based triggering mechanism without incorporation of a feedback from the FC and/or implementation of a local filter at the sensor level. We propose a multi-sensor triggering approach based on the projection of each local observation into the state-space which corresponds to the achievable gain in the sensor's information state vector. The simulation results show that the proposed multi-sensor information-based triggering mechanism closely follows its full-rate estimation counterpart.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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