Bibliographic record
Abstract
This article describes six examples of innovative planning and development in the Twin Cities metropolitan area. Although the locations vary considerably in age and location, they all provide gathering places for residents and visitors and express the Twin Cities' unique sense of place. One of the highlighted locations is Nicolette Mall, an 8-block pedestrian and bus mall through the retail core of Minneapolis. The Mall, which opened in 1967, has been renovated several times to improve the landscaping and attract shoppers and diners to the downtown area. Although there have been several proposals to return cars to the mall, residents have shown a strong preference for limiting the mall to pedestrian and bus only. Other locations highlighted in the article include: Excelsior and Grand, a mixed-use suburban development in Minneapolis; Jackson Meadow in the village of Marine on St. Croix, a housing development that bucks the McMansion trend to feature smaller homes clustered together; St. Paul's Upper Landing, which is the city's largest housing development and features a rivers' edge trail; three restored parks in downtown St. Paul; and Gold Medal Park, a 32-foot-high mound in Minneapolis that has a spiral path and grand view of the Mississippi River.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.006 |
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".