Environmental Damage in Riverside Communities of the Middle Course of the Araguari River Upstream from the Dam of the Cachoeira Caldeirão Hydroelectric Power Plant (HPP) Complex, in the Municipalities of Porto Grande/AP and Ferreira Gomes/AP
Bibliographic record
Abstract
This article aims to analyze the occurrence of environmental damage caused by the artificial reservoir of the Cachoeira Caldeirão Hydroelectric Power Plant (HPP) in the geographic area of the Bambu, Areia, Sapo Seco, and Capivara communities, located along the middle course of the Araguari River, in the rural zones of the municipalities of Porto Grande-AP and Ferreira Gomes-AP. The methodological procedures involved the selection, overlay, and analysis of satellite images through a remote sensing strategy, based on the reflectance and textures of the targets involved, in order to identify metrics and the period of occurrence. The study used photointerpretation of image textures and spectral responses of the analyzed targets, selecting satellite images available for the area of interest with different spatial, temporal, and spectral resolutions. A field survey was conducted in the Bambu, Areia, Sapo Seco, and Capivara communities to verify in loco the affected boundaries and the degree of forest degradation within areas of illegal deforestation. The field verification covered the entire perimeter of the area using GPS, along with photographic records. The results indicate that environmental damage has occurred, as reported by local riverine residents and confirmed through field inspections and temporal analysis using satellite imagery and the BCDCA Digital Terrain Model (DTM). These analyses demonstrate the rise in water levels, which has compromised crop cultivation, particularly cassava, a key crop for flour production, one of the staple foods for riverine communities.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".