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A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet
A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet
Summary
A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet is a scholarly article[1].
Key Facts
A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-deep-learning-based-mineral-prospectivity-modeling-framework-and-workflow-in-prediction-of-porphyryepithermal-minerali
MLA“A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-deep-learning-based-mineral-prospectivity-modeling-framework-and-workflow-in-prediction-of-porphyryepithermal-minerali.
BibTeX@misc{4ortxyz_a-deep-learning-based-mineral-prospectivity-modeling-framework-and-workflow-in-prediction-of-porphyryepithermal-minerali_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet}}, year = {2026}, url = {https://4ort.xyz/entity/a-deep-learning-based-mineral-prospectivity-modeling-framework-and-workflow-in-prediction-of-porphyryepithermal-minerali}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A deep-learning-based mineral prospectivity modeling framework and workflow in prediction of porphyry–epithermal mineralization in the Duolong ore District, Tibet — https://4ort.xyz/entity/a-deep-learning-based-mineral-prospectivity-modeling-framework-and-workflow-in-prediction-of-porphyryepithermal-minerali (retrieved 2026-05-24)
