An Intelligent Multi-hop Routing for Wireless Sensor Networks
Why this work is in the frame
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Bibliographic record
Abstract
With the advancement of micro-sensor and radio technology, wireless sensor networks are deployed in various applications. In a continuous monitoring application, sensors gather information and transmit the sensed data to base station in a periodic manner. In each data gathering round, a node generates a data packet and transmits the packet to base station, or any other node; the data packets received from neighbouring nodes can be aggregated. The lifetime of such sensor system is the time until base station receives data from all sensors in the network. We propose a genetic algorithm (GA) based multi-hop routing for a homogeneous network to maximize the network lifetime. Given the location of the sensor nodes and base station, our algorithm generates a sequence of routing paths that maximizes the system lifetime
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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 | 0.000 | 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