Visual impact produced by mining activity in the Punta Gorda ore body, Moa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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 it