Radar Task Scheduling with Gaussian Random Shifted Start Time
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
A radar task scheduling algorithm, Gaussian random shifted start time (GRSST), is proposed. The algorithm shifts each task's start time by a Gaussian distribution instead of a uniform distribution within the time window which was used in the random shifted start time (RSST) algorithm. Each task's priority is used to calculate its distribution variance. The random search is not related to the priorities. A higher priority task will have a smaller variance, so that its movable range is less than that of a lower priority task. Similar to the RSST, multiple searches help to find the solution with the lowest cost. Monte Carlo simulations show that the GRSST reduces the cost significantly with much less searches, which saves a lot of computation time too. The GRSST with 50 searches provides a better solution which costs around 2 times less than the RSST with 350 searches. The GRSST's average computation time is reduced to 1ms from 7ms.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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