An Application of Geographic Information System for Quarries Management
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
Geographic Information Systems (GIS) have evolved considerably, offering a wide range of applications.The flexibility of open-source software allows users to develop customized tools to address specific challenges in various fields [1].The availability of construction materials is essential for infrastructure development in any modern society [2].Therefore, quarries represent a field of study where the effectiveness of GIS can significantly optimize operations.In the mining sector, available programs and tools are often complex, especially when dealing with 3D models or advanced algorithms.Additionally, quarry operations require more accessible and agile solutions that enable users to efficiently handle spatial data and obtain real-time results for operational decision-making [3].Furthermore, effective quarry management is essential for mitigating environmental impacts and maximizing short and long-term sustainability.Our approach focuses on implementing a block model in a GIS, which integrates relevant information for quarry management and can be used in short-, medium-, and long-term mine planning [4].This will provide users with quick access to data related to production, product quality, consumption, and socio-environmental impacts, as well as the quality of the rock being excavated.The results will facilitate visualization through tables, graphs, and maps of the current or future state, excavation progress, or possible mining strategies.GIS can contribute to quarry management through results that provide a clear view of operation evolution and allow the identification of areas for improvement and optimization opportunities, in addition to a reduction in impacts such as emissions of gases into the atmosphere from loading or transportation stages [5], [6].The ability to access accurate data on consumption and emissions quickly and efficiently provides users with the opportunity to make well-versed decisions that drive operational efficiency improvement and promote the use of practices aligned with the concept of green mining.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 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 it