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Record W7082973391 · doi:10.33271/crpnmu/81.028

Assessment of mineral resources for Yukon’s gold mining district using GIS technologies

2025· article· en· W7082973391 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCollection of Research Papers of the National Mining University · 2025
Typearticle
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGeographic information systemMineral resource classificationMineral explorationGold miningResource (disambiguation)Natural resourceInformation extractionVisualizationProspection

Abstract

fetched live from OpenAlex

Purpose. To develop a methodological approach to the assessment of mineral resources of the Yukon gold mining region using modern geoinformation technologies (GIS). The methodology used: 3D modeling of mineral deposits. Results. A visualization of a mineral map was created using a geoinformation model of the deposit. A cartographic analysis of the Yukon gold mining region was performed, including a detailed location of deposits and potential mining areas. A mineral resource distribution model was formed for the assessment of gold reserves using GIS technologies. Originality. The scientific novelty lies in the integration of multidimensional data and high-tech algorithms to create visually understandable models of mineral distribution. This contributes not only to more effective planning of mining operations, but also provides the opportunity to take into account environmental factors for more sustainable management of natural resources. In addition, the proposed methodology can be adapted for different types of minerals and geographical conditions, which makes it a universal tool in geological exploration and reserve assessment. This opens up new prospects for the use of GIS technologies in the mining industry. Practical value. Thanks to the use of multidimensional data analysis, it is possible to minimize the risks of errors and optimize the mining process, reducing the costs of drilling and exploration. In addition, the detailing of underground structures allows you to take into account environmental factors, choosing mining areas with minimal impact on nature. The versatility of the method ensures the possibility of its adaptation to the extraction of various minerals and conditions, which makes it an important tool for the development of the modern mining industry. The implementation of this approach will contribute to sustainable management of natural resources and increasing the environmental responsibility of the industry.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.357
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it