A Framework for Multifunctional Green Infrastructure Investment in Camden, NJ
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study demonstrates a decision-support framework for planning Green Infrastructure (GI) systems that maximize urban ecosystem services in Camden, NJ. Seven key ecosystem services are evaluated (urban agriculture expansion, combined sewer overflow reduction, heat island reduction, flooding reduction, capacity building/green jobs expansion, fitness expansion, and stress reduction), to produce a normalized value for each service for each drainage sub-basin within the city. Gaps in ecosystem services are then mapped and utilized to geographically prioritize different kinds of multifunctional GI. Conceptual designs are developed for four site typologies: parks, schools, vacant lots, and brownfield sites. For one demonstration site, additional analysis is presented on urban engagement, life cycle cost reduction, and new sources of funding. What results is an integrated, long-term vision where multifunctional GI systems can be readily customized to meet multiple needs within urban communities. This study provides a portable and replicable framework for leveraging the regulatory requirement to manage stormwater to meet broader urban revitalization goals, all through a decentralized network of green infrastructure assets.
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.
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 it