Reclamation of Derelict Industrial Land in Portugal: Greening is not Enough
Bibliographic record
Abstract
A negative effect of the globalization on industry over the past decades was a vast array of obsolete industrial facilities and the various impacts, which were generated from them.In this context, abandonment, sale or demolition of such facilities, were fairly common approaches.However, the creation of new and more severe environmental legislation, the high price of urban land, and the public pressure related with the need to protect the environment, increased the number of post-industrial sites that returns to productive use.Within every problem there is an opportunity.Derelict and contaminated industrial sites have high potential for urban regeneration, ecological restoration and reintegration into the surrounding community.To exemplify the importance of those spaces in the urban landscape, this paper will analyze two industrial reclamation projects realized in Portugal during the last decade (Parque Tejo-Trancão -Expo 98 and Braga Stadium -Euro 2004).The significance of these projects in achieving a sustainable urban landscape is discussed.This article shows that the industrial landscape should be viewed as a resource and its recovery as an opportunity to develop new multifunctional landscapes in which new forests are indispensable.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".