Bibliographic record
Abstract
System Summary Baltimore is an old East Coast city that is diverse not only in its population but also in its infrastructure. The Department of Public Works--Bureau of Water and Wastewater Bureau is responsible for maintaining three of the four city-owned and city-operated utilities. These include the water distribution, storm water, and wastewater collection systems. While the storm water and wastewater collection systems are confined to the city's corporate limits, the water distribution system extends well beyond and services a large portion of neighboring Baltimore County. With systems as complex and extensive as Baltimore's, there is a continuous need to provide large amounts of information to maintenance crews, engineers, designers, consultants, contractors, and the public. This effort has at times been both frustrating and time-consuming for employees, professionals, and homeowners alike. The fact that each utility had its own map scales, naming conventions, and tiling schemes only compounded the problem. With more than a quarter million documents to manage related to the utility infrastructure, records research and timely access to accurate information required for proper decision making have been difficult to provide. Change was needed. Technology and time were the keys to that change. Utility-related Geographic Information System (GIS) development began in earnest in the late 1990s with the typical aerial photography, stereo compilation, and conversion of paper records. This effort was completed in early 2000. At that time, ArcIMS development and system-support requirements made any application development unfavorable. Finally, in 2003, funding and network infrastructure came together, which permitted the establishment of servers running ArcIMS and Oracle/SDE. With the development of U-View, the city can now take advantage of GIS and Internet technologies to provide available tabular, geographical, and image-related data to any user at any PC within the city. No longer are employees tied to their respective offices where the information resided. The loss in productivity resulting from staff having to travel to dispersed locations to retrieve paper records is being eliminated. As an unexpected bonus to the development effort, the application has been found to work exceptionally well with wireless technologies, which will add significant value to the city's investment by allowing maintenance managers, complaint scouts, engineers, and other city managers access to the vast infrastructure data sets in real time, in the field, at the site where timely and accurate emergency decisions, based on real information, need to be made. What makes U-View exemplary and unique within the region is its ability to deliver a variety of utility-related information to a multitude of users at varying levels of city government. From information desk attendants, permit reviewers, and maintenance crews through engineers and appointed decision makers, U-View provides easy and timely access to the information needed for making better decisions related to utility infrastructure management. Motivation for System Development As with most governments, both large and small, in today's economic environment, the biggest motivation is cost and the need to reduce those costs for our constituents. The resounding theme heard in nearly every discussion of budgets is do more with less--less equipment, less staff, less money, but not less services. Given these orders, the natural solution becomes greater use of automation and technology when performing routine manual tasks. The general reduction in man-hours related to records research and retrieval while maintaining or improving records access was the motivation and goal related to the development of U-View. An additional motivation was the need to replace an obsolete version of a desktop-based system that is no longer supported by the vendor. …
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 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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".