Item talk:Q319874

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 "DOI": {
   "doi": "10.5066/p9fxspt1",
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       "name": "Margaret A Goldman",
       "nameType": "Personal",
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         "United States Geological Survey"
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     {
       "name": "Joshua M Rosera",
       "nameType": "Personal",
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         "United States Geological Survey"
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     },
     {
       "name": "Graham W Lederer",
       "nameType": "Personal",
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         "United States Geological Survey"
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     {
       "name": "Garth E Graham",
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         "United States Geological Survey"
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           "nameIdentifier": "https://orcid.org/0000-0003-0657-0365",
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     },
     {
       "name": "Asitang Mishra",
       "nameType": "Personal",
       "affiliation": [
         "NASA Jet Propulsion Laboratory"
       ],
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     {
       "name": "Alice Yepremyan",
       "nameType": "Personal",
       "affiliation": [
         "NASA Jet Propulsion Laboratory"
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   ],
   "titles": [
     {
       "title": "Training and validation data from the AI for Critical Mineral Assessment Competition"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2023,
   "subjects": [
     {
       "subject": "geography"
     },
     {
       "subject": "mineral resources"
     },
     {
       "subject": "economic geology"
     }
   ],
   "contributors": [],
   "dates": [],
   "language": null,
   "types": {
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   "descriptions": [
     {
       "description": "Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training and validation data from the competition are provided here, as well as competition details and baseline solutions. The data are derived from published sources and are provided to the public to support continued development of automated georeferencing and feature extraction tools. References for all maps are included with the data.",
       "descriptionType": "Abstract"
     }
   ],
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   "created": "2023-12-27T21:47:59Z",
   "registered": "2023-12-27T21:47:59Z",
   "published": null,
   "updated": "2023-12-27T21:48:07Z"
 }

}