Low Impact Development and Transportation in the City of Mesa, AZ
Bibliographic record
Abstract
The Cities of Mesa and Glendale, with a grant from the Water Infrastructure Finance Authority of Arizona (WIFA), partnered and developed a Low Impact Development (LID) Toolkit. This toolkit is a 100 page document that responds to the need to better manage the storm water runoff and reduce the need for very expensive expansion of drainage infrastructure. The solution to this problem justifies the need to use LID in Mesa. In 2014 the City of Mesa experienced flooding which affected many. Although LID solutions was considered at the time of this flooding event, it became a priority to identify potential solutions. The LID toolkit responded to this and is intended to minimize the harmful impacts of flooding by setting best practices related to the management of the rainfall-runoff process. The LID toolkit identifies and lists best storm-water City of Mesa management practices and national and regional LID best practices. This list and publication is intended to encourage City and private planners, designers and residents alike towards the practice of more sustainable design. The article presents the history of LID design and discusses the benefits of using LID tools.
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 | 0.000 | 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 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".