General Framework of Quantitative Target Selections Article Swipe
Mineral target selection has been an important research subject for geoscientists around the world in the past three decades. Significant progress has been made in development of mathematical techniques and estimation methodologies for mineral mapping and resource assessment. Integration of multiple data sets, either by experts or statistical methods, has become a common practice in estimation of mineral potentials. However, real effect of these methodologies is at best very limited in terms of uses for government macro policy making, resource management, and mineral exploration in commercial sectors. Several major problems in data integration remain to be solved in order to achieve significant improvement in the effect of resource estimation. Geoscience map patterns are used for decision-making for mineral target selections. The optimal data integration methods proposed so far can be effectively applied by using GIS technologies. The output of these methods is a prognostic map that indicates where hidden ore bodies may occur. Issues related to randomness of mineral endowment, intrinsic statistical relations, exceptionalness of ore, intrinsic geological units, and economic translation and truncation, are addressed in this chapter. Moreover, a number of specific important technical issues in information synthesis are also identified, including information enhancement, spatial continuity, data integration and target delineation. Finally, a new concept of dynamic control areas is proposed for future development of quantification of mineral resources.
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- Type
- book-chapter
- Language
- en
- Landing Page
- https://doi.org/10.1007/978-3-319-78999-6_21
- https://link.springer.com/content/pdf/10.1007%2F978-3-319-78999-6_21.pdf
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https://doi.org/10.1007/978-3-319-78999-6_21Digital Object Identifier
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General Framework of Quantitative Target SelectionsWork title
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book-chapterOpenAlex work type
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enPrimary language
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2018Year of publication
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2018-01-01Full publication date if available
- Authors
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Guocheng PanList of authors in order
- Landing page
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https://doi.org/10.1007/978-3-319-78999-6_21Publisher landing page
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https://link.springer.com/content/pdf/10.1007%2F978-3-319-78999-6_21.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007%2F978-3-319-78999-6_21.pdfDirect OA link when available
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Computer science, Data integration, Resource (disambiguation), Data mining, Randomness, Mineral resource classification, Estimation, Data science, Management science, Operations research, Systems engineering, Engineering, Geology, Mathematics, Statistics, Geochemistry, Computer networkTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2023: 2, 2022: 1, 2021: 1, 2019: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.resources. | 220 |
| abstract_inverted_index.techniques | 28 |
| abstract_inverted_index.Integration | 38 |
| abstract_inverted_index.Significant | 19 |
| abstract_inverted_index.assessment. | 37 |
| abstract_inverted_index.continuity, | 197 |
| abstract_inverted_index.development | 25, 215 |
| abstract_inverted_index.effectively | 130 |
| abstract_inverted_index.estimation. | 108 |
| abstract_inverted_index.exploration | 83 |
| abstract_inverted_index.identified, | 192 |
| abstract_inverted_index.improvement | 102 |
| abstract_inverted_index.information | 188, 194 |
| abstract_inverted_index.integration | 92, 123, 199 |
| abstract_inverted_index.management, | 80 |
| abstract_inverted_index.potentials. | 58 |
| abstract_inverted_index.selections. | 119 |
| abstract_inverted_index.significant | 101 |
| abstract_inverted_index.statistical | 47, 161 |
| abstract_inverted_index.translation | 171 |
| abstract_inverted_index.truncation, | 173 |
| abstract_inverted_index.delineation. | 202 |
| abstract_inverted_index.enhancement, | 195 |
| abstract_inverted_index.mathematical | 27 |
| abstract_inverted_index.geoscientists | 10 |
| abstract_inverted_index.methodologies | 31, 64 |
| abstract_inverted_index.technologies. | 135 |
| abstract_inverted_index.quantification | 217 |
| abstract_inverted_index.decision-making | 115 |
| abstract_inverted_index.exceptionalness | 163 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5021283712 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 1 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/8 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Decent work and economic growth |
| citation_normalized_percentile.value | 0.66246747 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |