Solution Space for Fixed-Priority with Preemption Threshold
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
This paper reaffirms that fixed-priority with preemption threshold (FPPT) is an important form of real-time scheduling algorithm, which fills the gap between fixed-priority preemptive (FPP) and fixed-priority nonpreemptive (FPNP). When a task set is schedulable by FPPT, there may exist multiple valid preemption threshold assignments, which provide useful scheduling options. All valid assignments form a solution space that is delimited by a minimal and maximal assignment. A mechanism is presented to generate part of the valid assignments once the minimal and maximal assignments are known. The known algorithm to compute the minimal assignment starts at FPP, and the known algorithm to compute the maximal assignment starts from any valid assignment. This paper presents algorithms to compute the minimal and maximal assignments starting from FPNP, and the proofs for the correctness of these algorithms are also presented.
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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 | 0.001 |
| 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