[{"data":1,"prerenderedAt":82},["ShallowReactive",2],{"ki-evidenznetz-dossier-output-67af2c6b0b745cec57fc55c2-63fe68b9":3},{"edges":4,"entity":16,"fingerprint":43,"generatedAt":44,"neighbors":45,"schemaVersion":81},[5],{"evidence":6,"evidenceClass":11,"from":12,"id":13,"relation":14,"to":15},{"dataset":7,"field":8,"sourceId":9,"url":10},"german-ai-research-to-transfer-index","cordis_project_code","101121135:output:67af2c6b0b745cec57fc55c2","https:\u002F\u002Fcordis.europa.eu\u002Fproject\u002Fid\u002F101121135","exact","cordis:101121135","edge:project-output:101121135:67af2c6b0b745cec57fc55c2","has_observed_output","output:67af2c6b0b745cec57fc55c2",{"attributes":17,"edgeCount":27,"id":15,"indexable":19,"label":28,"links":29,"slug":38,"sourceRefs":39,"type":42},{"citationCount":18,"isOpenAccess":19,"openAireId":20,"outputType":21,"persistentIdentifiers":22,"publicationDate":26},0,true,"doi_________::14cd25f82ec960394e6d8d6b2712a86c","publication",[23],{"scheme":24,"value":25},"doi","10.5194\u002Fegusphere-2026-1253","2026-03-19",1,"Using machine learning for the prediction of flood-related 112 calls",[30,34],{"kind":31,"label":32,"url":33},"official_source","OpenAIRE","https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_________%3A%3A14cd25f82ec960394e6d8d6b2712a86c",{"kind":35,"label":36,"url":37},"persistent_identifier","DOI 10.5194\u002Fegusphere-2026-1253","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fegusphere-2026-1253","output-67af2c6b0b745cec57fc55c2-63fe68b9",[40],{"dataset":7,"field":41,"sourceId":20,"url":33},"openaire_research_product_id","output","sha256:4af92aa83acf606b3c3e7fb77c284715025099eebbb93351581bb39479425dab","2026-09-26T08:35:38.651Z",[46],{"attributes":47,"description":65,"edgeCount":66,"id":12,"indexable":19,"label":67,"links":68,"slug":75,"sourceRefs":76,"type":80},{"acronym":48,"code":49,"endDate":50,"frameworkProgramme":51,"funding":52,"knowledgeFlow":56,"research":57,"startDate":64},"GOBEYOND","101121135","2027-09-30","HORIZON",{"currency":53,"germanNetEuContributionCents":54,"participantEdgeCount":27,"status":55},"EUR","12600000","linked",null,{"citationDataOutputCount":58,"citedOutputCount":59,"firstPublicationDate":60,"lastPublicationDate":26,"openAccessOutputCount":61,"outputCount":58,"status":55,"totalCitations":62,"typeCounts":63},14,9,"2024-06-17",13,50,{"dataset":18,"other":18,"publication":58,"software":18},"2023-10-01","GeO and weather multi-risk impact Based Early warning and response systems supporting rapid deploYment of first respONders in EU and beyonD",12,"GOBEYOND · GeO and weather multi-risk impact Based Early warning and response systems supporting rapid deploYment of first respONders in EU and beyonD",[69,71],{"kind":31,"label":70,"url":10},"CORDIS",{"kind":72,"label":73,"url":74},"local_dossier","KI-Innovationspfad","\u002Ftools\u002Fki-innovationspfad\u002F?project=101121135","project-cordis-101121135-b35ea4ee",[77],{"dataset":78,"field":79,"sourceId":12,"url":10},"german-ai-innovation-path","cordis_project_id","project","ki-evidenznetz.entity.v1",1790412363089]