Proposal for a Mining-Touristic Route in Parque Minero Industrial Mochuelo Bajo, Bogota. A Look from the Environmental, Social and Productive Factor
Bibliographic record
Abstract
Minerals extraction processes are the foundation on which industrial societies are sustained. In Bogotá, the park Mochuelo Bajo emerges as an area of clay exploitation for the production of construction materials. This article aims to discover the geo-touristic potential of the area through the Integrated Approach for Assessing the Geotourism method. In addition, the investigation proposes the creation of a possible tourist route and the analysis of opportunities, strengths, weaknesses and threats in the area, in order to implement this proposal and to calculate the cost of the tour. The methodology consisted of a mixed approach with an exploratory scope, using as data sources, interviews, tours of the area, non-participant observation and secondary data, which were collected from the mines as well as from the inhabitants of the study area and in official information sources. The results obtained indicate the mining proposal has a high potential and so, the possible threats and weaknesses could be handled through administrative controls. Additionally, it was possible to locate a route with five areas to be intervened, and where the importance of clay in production processes, the different materials obtained from this, as well as the industrial evolution in the sector is highlighted.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".