Introduction to the special section on the Fifth IEEE International Nanoelectronics Conference (IEEE INEC)
Bibliographic record
Abstract
The Guest Editors are pleased to present here a special section of the best papers selected from 242 presentations in the fifth IEEE International Nanoelectronics Conference (IEEE INEC) held in Singapore in January 2013. The theme of the INEC 2013 is "sustainable nanoelectronics," aiming in nanoelectronics for the future. It brought together more than 230 participants to Singapore from 23 countries over the world, including China, Japan, Korea, India, Thailand, Egypt, Iran, Australia, Sweden, Canada, US, France, and UK. In addition to the invited and contributed talks and poster session, the conference also invited renowned experts to give keynote speech, spreading out in four parallel symposia: 1) Nanofabrication; 2) Nanoelectronics; 3) Nanophotonics; and 4) Nanosciences. We believe that the papers selected for this special section reflect the high quality of research in nanotechnology, and they will undoubtedly benefit the researchers in the field for their research and manufacturers for developing new high technology products.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.146 | 0.087 |
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".