Visual impact produced by mining activity in the Punta Gorda ore body, Moa
Bibliographic record
Abstract
Open-pit mining has adverse impacts on the landscape of the mining area. This article describes the visual impact resulting from surface mining activities being conducted in the Punta Gorda laterite ore body located in Moa. The implementation of the indirect method Bureau of Land Management by means of computer tools, such as Surfer 8.0, Didger 3.02, Gemcom 4.11, Autocad Civil 3d allowed the determination of visual landscape units and the main visual basins according to the method of selection used. This investigation also includes an analysis on the visual basin soil, color, texture and luminosity. Observation locations were selected based on their topographical characteristics or because of their being located in the highest altitudes. It was concluded that the visual impact of mining activities on the landscape investigated covers more than 50% of the visual basin. This research paves the way to a new field in the visual impact assessment of open-pit mining in Cuba. It constitutes a practical contribution providing information of interest on landscapes for the decision making associated with ore body management and planning and it stands out for being useful to ensure a successful mining and environmental planning of a region.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".