Proceedings of the 1st ACM international workshop on Foundations of wireless ad hoc and sensor networking and computing
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
It is our great pleasure to welcome you to the 2nd ACM International Workshop on Foundations of Wireless Ad Hoc and Sensor Networking and Computing (ACM FOWANC'09), which takes place in New Orleans on May 18, 2009. With the success of ACM FOWANC'08 at Hong Kong last year, we are delighted to continue this workshop with ACM MobiHoc 2009 and hope it will become a regular ACM MobiHoc workshop in the following years. ACM FOWANC'09 is devoted to distributed algorithms and theoretical methods in the context of wireless ad hoc and sensor networking and computing. This workshop is intended to foster cooperation among researchers in wireless ad hoc and sensor networking and theoreticians in algorithm and theory, and push the theoretical research forward for a deeper understanding about ad hoc and sensor networking and computing. This year, ACM FOWANC received less submissions than last year, however, the overall quality of submissions was excellent. Most of the papers received three peer reviews from our technical program committee (TPC), comprising people from industry, national laboratories, and universities all over the world. After a thorough analysis of the reviews returned, we accepted 10 regular papers for the workshop. The final workshop program includes three technical sessions and one keynote address. We are honored to have Prof. Jie Wu from Florida Atlantic University to give an opening keynote address, titled as On Self-Organization in MANETs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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