MINING IN CARBONATE ROCKS IN THE METROPOLITAN REGION OF CURITIBA, PR: CHALLENGES FOR THE PRESERVATION OF KARST AND SPELEOLOGICAL HERITAGE
Bibliographic record
Abstract
Carbonate rocks are the lithotypes with the highest volume of exploitation and financial profitability in the Metropolitan Region of Curitiba (RMC), representing the most important mineral source for the cement industry, aggregates in construction, soil acidity correction, as well as housing the Karst Aquifer of the RMC, ornamental rock mines, and providing inputs for the manufacturing industry. However, mining activity, carried out in open-pit operations through the dismantling of rock masses usually using explosives, directly impacts the karst landscape and regional speleological heritage, especially the dozens of caves occurring in the region. Therefore, considering the irreversible nature of the environmental impacts resulting from mining and the lack of continuous monitoring of mined areas, remote sensing data, official mining data, and records of environmental damage were used to identify the growth of carbonate rock mining and its impacts on regional karst and speleological heritage. Specifically, the following data were used: records from the National Mining Agency (ANM), historical records from the Paraná Speleological Studies Group (GEEP-Açungui), and primarily, 1980-2022 land use and land cover change dataset derived from Landsat 5, 7, and 8 series of images. The increase in the land use classified as "mining" between 1980 and 2022, the annual increase in revenue from the Financial Compensation for Mineral Exploration, and the presence of dozens of caves in areas with active mining processes allowed for identifying that the growth of mining activity in carbonate rocks constitutes the greatest challenge to preserving the karst systems of the RMC.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".