Bibliographic record
Abstract
On behalf of the Technical Program Committee, we welcome all of you to the 13thIEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC 2017) in the beautiful Valencia, Spain! We are indeed delighted that this year's IEEE IWCMC accomplishes its goal under the conference theme “Plethora Communications” and continues its tradition of providing a premier forum for presentation of research results and experience reporting on the cutting edge research in the general areas of wireless communications and mobile computing. This year, we received more than 900 submissions from 32 countries. Each paper received at least three peer technical reviews, comprised of more than 500 TPC members from academia, government laboratories, and industries. After carefully examining all review reports, the IEEE IWCMC 2017 TPC finally selected about 36% high-quality papers for presentation at the conference and publication in the IEEE IWCMC 2017 proceedings.
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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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.021 | 0.027 |
| Insufficient payload (model declined to judge) | 0.062 | 0.086 |
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".