Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments
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 1st ACM International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments -- MELT'08. Location-awareness is a key component for achieving context-awareness. Recent years have witnessed an increasing trend of location-based services and applications. In most cases, however, location information is limited by the accessibility to GPS, which is unavailable for indoor or underground facilities and unreliable in urban environments. Much research has been done, in both the sensor network community and the ubiquitous computing community, to provide techniques for localization and tracking in GPS-less environments. Novel applications based on ad-hoc localization and real-time tracking of mobile entities are growing as a result of these technologies. It is time to bring leaders from both the academic and industrial research communities to discuss challenging and open problems, to evaluate pros and cons of various approaches, to bridge the gap between theory and applications, and to envision new research opportunities in MELT. The call for papers attracted 38 submissions from Asia, Canada, Europe, and the United States. The program committee accepted 14 papers for oral presentations and 9 papers for poster presentations. The workshop consists of four technical sessions and three poster sessions, with topics covering areas of optimization and signal processing techniques, novel radio signal strength based methods, as well as systems and applications in MELT.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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