INNOVATION THE PRACTICES OF CONSTRUCTION OF SUSTAINABLE NEIGHBORHOODS: JARDIM DAS PERDIZES, SÃO PAULO – BRAZIL
Bibliographic record
Abstract
The growth of the population's demand for urbanization besides the globalization of the economy and technology, leads to the depletion of natural resources, requiring a new vision of business focused on sustainability. In this scenario, the Civil construction has been acting in a participatory way in designing and thinking, aiming to reduceimpacts to the environment. The Jardim das Perdizes neighborhood, located in the Barra Funda region of São Paulo, is the first to receive the AQUA certification of sustainable neighborhood, and has several constructive techniques and equipment bringing improvement and economics of the use of natural resources, with Predictedrates of reduction of 35% of water consumption and 25% of energy consumption, in addition to the high performance of buildings, spaces and equipment. Moreover, within the undertaking there is also a park donated to the public sector with complete infrastructure, integrating the leisure space with the interrelations of society andthe ways of thinking sustainability. It is possible to observe with the study that the actions of fostering sustainable constructions benefit the environment with the reduction of raw material consumption and non-renewable resources, to the population with more planned and better income spaces and to the market Real estate, valuingbuildings.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".