Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Bibliographic record
Abstract
Welcome to ACM MobiCom 2007, the Thirteenth Annual International Conference on Mobile Computing and Networking, in Montreal, Canada. Continuing the tradition of one of the premier conferences in mobile networking, we have an exciting program on offer with papers, posters and panel, representing the best of today's research in mobile networking and computing!. We received 233 paper submissions from 28 countries, out of which 26 papers were accepted as full papers and 14 papers were accepted as Extended Abstracts to be presented as posters. The quality of papers was outstanding as usual, forcing many hard choices on the Technical Program Committee (TPC). To select the papers, we employed a three-phase process. First, the TPC selected papers from an access-controlled web site and provided reviews; then, we had an online discussion phase that selected about 80 papers for more detailed discussion; finally, we had a TPC meeting in Evanston, Illinois to discuss and select 40 papers for inclusion in the program, either as full papers or Extended Abstracts. The review process was double blind and every paper received at least three reviews, many received four, and some received five reviews. As in previous years, we have a Best Student Paper Award. The selection of the best student paper was done in two stages. First, a TPC sub-committee consisting of Farooq Anjum, Suman Banerjee, Sneha Kasera, Ben Liang and Mehul Motani short-listed candidate papers from among all full papers whose primary author was a student. These papers were reviewed in more detail, and discussed, after which consensus was reached on the winning paper. The MobiCom '07 Best Student Paper award goes to Crossing Over the Bounded Domain: From Exponential To Power-law Inter-meeting Time in MANET by Han Cai and Do Young Eun from North Carolina State University. Our congratulations to the authors. Coming to the technical program, we have a wide variety of papers and posters organized into eight sessions over three days. These include poster presentations of Extended Abstracts as well as student posters and demonstrations that were selected using a separate process from the papers. One of the sessions is dedicated to Challenge papers that describe revolutionary new approaches, technologies or visions to stimulate new research directions. We hope that you will find the MobiCom '07 technical program helpful in your research.
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.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.154 | 0.113 |
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".