Keynote Speech 1: Wireless power harvesting and transfer
Bibliographic record
Abstract
Electromagnetics forms the foundation of modern electrical and electronic systems that see the technologies we enjoy and take for granted today. It has been used to transfer information and power in daily lives. In the wireless domain, however, it had not been considered and employed much for power transfer until 2008 when a MIT research team lead by Prof. Marin Soljacic successfully demonstrated the mid-range wireless power. Since then, many efforts and much progress have been made to improve power transfer efficiency, reduce system size and include more functionality; the goal is to cut the last wires in electrical and electronic devices and systems if all possible. In this talk, we will first present the principles of the wireless power harvesting and transfer and then focus on mid-range wireless power transfer and its applications and commercialization. We will present the challenges, progresses, and future directions in the areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.096 | 0.057 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".