A model for battery lifetime analysis for organizing applications on a pocket computer
Why this work is in the frame
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Bibliographic record
Abstract
A battery-powered portable electronic system shuts down once the battery is discharged; therefore, it is important to take the battery behavior into account. A system designer needs an adequate high-level battery model to make battery-aware decisions targeting the maximization of the system's online lifetime. We propose such a model that allows a designer to analytically predict the battery time-to-failure for a given load. Our model also allows for a tradeoff between the accuracy and the amount of computation performed. The quality of the proposed model is evaluated using typical pocket computer applications and a detailed low-level simulation of a lithium-ion electrochemical cell. In addition, we verify the proposed model against actual measurements taken on a real lithium-ion battery.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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