Item talk:Q324453

{

 "DOI": {
   "doi": "10.5066/p9zd9gvz",
   "identifiers": [],
   "creators": [
     {
       "name": "Wiens, Ashton M",
       "nameType": "Personal",
       "givenName": "Ashton M",
       "familyName": "Wiens",
       "affiliation": [
         "United States Geological Survey"
       ],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0002-7030-0602",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Thogmartin, Wayne E",
       "nameType": "Personal",
       "givenName": "Wayne E",
       "familyName": "Thogmartin",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0002-2384-4279",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     }
   ],
   "titles": [
     {
       "title": "R code to fit Gaussian process models to white-nose syndrome/Pseudogymnoascus destructans monitoring data across North America from 2006-2022"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2022,
   "subjects": [],
   "contributors": [],
   "dates": [
     {
       "date": "2022",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
     "schemaOrg": "Dataset",
     "resourceType": "Dataset",
     "resourceTypeGeneral": "Dataset"
   },
   "relatedIdentifiers": [
     {
       "relationType": "IsCitedBy",
       "relatedIdentifier": "10.1002/ece3.9547",
       "relatedIdentifierType": "DOI"
     }
   ],
   "relatedItems": [],
   "sizes": [],
   "formats": [],
   "version": null,
   "rightsList": [],
   "descriptions": [
     {
       "description": "This code supports the manuscript \"Gaussian process forecasts Pseudogymnoascus destructans will cover coterminous United States by 2030.\" The code is used to fit Gaussian process models to publicly accessible monitoring data on the spread of white-nose syndrome in North America. These models are used to make predictions on a fine spatial grid, giving a forecast (and hindcast) of the spread of white-nose syndrome at any location. Also contained in the code is a retrospective cross validation experiment, producing parameter estimates and model scoring over time. The code also relies on the GRTS grid for model prediction, which is publicly accessible at https://doi.org/10.5066/p9o75ydv. Shapefiles such as administrative boundaries can be used to add to plots are not required for the analysis.",
       "descriptionType": "Abstract"
     }
   ],
   "geoLocations": [],
   "fundingReferences": [],
   "url": "https://www.sciencebase.gov/catalog/item/634e9f6cd34e47431c154384",
   "contentUrl": null,
   "metadataVersion": 1,
   "schemaVersion": "http://datacite.org/schema/kernel-4",
   "source": "mds",
   "isActive": true,
   "state": "findable",
   "reason": null,
   "viewCount": 0,
   "downloadCount": 0,
   "referenceCount": 0,
   "citationCount": 1,
   "partCount": 0,
   "partOfCount": 0,
   "versionCount": 0,
   "versionOfCount": 0,
   "created": "2022-11-10T13:43:46Z",
   "registered": "2022-11-10T13:43:47Z",
   "published": null,
   "updated": "2023-03-05T04:58:21Z"
 }

}