Item talk:Q326725

From geokb

{

 "DOI": {
   "doi": "10.5066/p9676o1m",
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       "name": "DeAngelo, Jacob",
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       "name": "Earney, Tait E",
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       "givenName": "Tait E",
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       "name": "Dean, Branden J",
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       "name": "Zielinski, Laurie A",
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       "name": "Ritzinger, Brent T",
       "nameType": "Personal",
       "givenName": "Brent T",
       "familyName": "Ritzinger",
       "affiliation": [],
       "nameIdentifiers": []
     }
   ],
   "titles": [
     {
       "title": "USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics Data"
     }
   ],
   "publisher": "U.S. Geological Survey",
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     "identifier": "https://doi.org/10.5066/P9V5SQRD",
     "identifierType": "DOI"
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   "publicationYear": 2021,
   "subjects": [
     {
       "subject": "faulting (geologic), geophysics, geothermal resources, gravitational field (earth), magnetic field (earth), natural resource assessment"
     }
   ],
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   "dates": [
     {
       "date": "2021",
       "dateType": "Issued"
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   "descriptions": [
     {
       "description": "This package contains gravity and magnetics data and products generated for the Nevada Machine Learning (NVML) project (DE-FOA-0001956). Data products contained in this release consist of grids and vector data. Grids include: primary anomaly maps (isostatic and PSG), match-filtered maps, horizontal gradient (HG) maps, confidence maps, and maps showing density of specific key structural features. The vector data in this release include the gravity stations, HGM of gravity and magnetics, ?generalized? lineations for gravity and magnetics, gravity and magnetic lineation terminations and intersections, and ?well-constrained? HGM saddles.",
       "descriptionType": "Abstract"
     }
   ],
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   "created": "2021-11-30T18:29:07Z",
   "registered": "2021-11-30T18:29:08Z",
   "published": null,
   "updated": "2022-03-02T23:38:35Z"
 }

}