Optimal Unlimited Free-Replacement Warranty Strategy using Reconditioned Products
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
The long-term sustainability of our resources is dependent on reducing the consumption of virgin resources, and one method of achieving this goal is product remanufacturing. It is already established that the production of remanufactured products costs less than that of creating a new one, however the effects of this on warranty costs are now considered. Due to consumer perceptions of the quality of remanufactured products, it cannot be sold for the same price as a new product. In addition, the warranty costs the manufacturer incurs will also be higher. This paper proposes a mathematical model for the optimal one-dimensional unlimited free-replacement warranty policy with replacements carried out with reconditioned products. Numerical optimization is used to compute the optimal warranty and production parameters which maximize the total profit.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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