Bibliographic record
Abstract
After years of decline, the city of Buffalo is looking forward to a bright future. The city has introduced a new comprehensive plan that offers a long-term vision for the city. The plan seeks to fix the basics and build on the assets of the city. The city offers many advantages: an easy-to-use street grid, grand parks, beautiful old houses, an active arts and culture scene, access to two Great Lakes and a location on an international border. However, the city also faces many challenges: an aging and oversized road system, the need to diversify its employment base, and the need to expand its tax base. To improve the city, an aggressive demolition plan has been implemented for some of the 5,000 abandoned buildings in the city. The city also plans to use $7 million in funding from the TEA-21 reauthorization to reopen Buffalo's Main Street, which was turned into a transit mall in the early 1980s. Plans are also underway to improve the U.S.-Canadian shared border. Planners hope these efforts will help revitalize Buffalo as a healthy, attractive and stable city.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.028 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.077 | 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".