UNIVERSITY OF CALGARY A Software Engine for the Rapid Development of Mobile Asset Management Systems
Bibliographic record
Abstract
Developments in computing, location and wireless technologies have caused great advances in the field of Location Based Services (LBS). A particular subset of LBS, Mobile Asset Management Systems (MAMS) has attracted the attention of industry because of its potential for improving productivity, safety and security. However, obstacles remain that have hindered the adoption of MAMS by corporations. These obstacles include the large number of technologies and providers that are available, plus the isolated nature of MAMS development that creates duplication of effort and resources. This research has focused on creating a development platform that offers the fundamental functionality required by MAMS, enabling developers to use it as a foundation for their applications while reducing duplication of efforts. This platform is created using Java and leverages object-oriented application frameworks to realize advantages in maintenance and ease of integration for developers. It offers two-way communication and control capabilities in conjunction with remote sensors and a widespread cellular network. Data management and storage capabilities are provided and
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".