CSciBox: Artificial intelligence for age-depth modeling
Artificial intelligence (AI) provides major opportunities for scientific analysis. Automated reasoners can explore problem spaces quickly and alert practitioners to possibilities that they had not considered. As a case in point, we describe the CSciBox system. Working with data from a paleorecord, s...
| Main Authors: | , , |
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| Format: | Text |
| Language: | unknown |
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CU Scholar
2018
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| Online Access: | https://scholar.colorado.edu/csci_facpapers/20 https://scholar.colorado.edu/cgi/viewcontent.cgi?article=1018&context=csci_facpapers |
| Summary: | Artificial intelligence (AI) provides major opportunities for scientific analysis. Automated reasoners can explore problem spaces quickly and alert practitioners to possibilities that they had not considered. As a case in point, we describe the CSciBox system. Working with data from a paleorecord, such as 14C dates from a sediment core (Fig. 1a) or 18O values from an ice core, CSciBox produces a set of age-depth models, plus a description of how each one was built and an assessment of its quality. |
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