Sufficient conditions for the value function and optimal strategy to be\n even and quasi-convex
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Bibliographic record
Abstract
Sufficient conditions are identified under which the value function and the\noptimal strategy of a Markov decision process (MDP) are even and quasi-convex\nin the state. The key idea behind these conditions is the following. First,\nsufficient conditions for the value function and optimal strategy to be even\nare identified. Next, it is shown that if the value function and optimal\nstrategy are even, then one can construct a "folded MDP" defined only on the\nnon-negative values of the state space. Then, the standard sufficient\nconditions for the value function and optimal strategy to be monotone are\n"unfolded" to identify sufficient conditions for the value function and the\noptimal strategy to be quasi-convex. The results are illustrated by using an\nexample of power allocation in remote estimation.\n
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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