[{"data":1,"prerenderedAt":95},["ShallowReactive",2],{"ki-evidenznetz-dossier-output-49534e44eb3e9feecd76cf40-4e1a25dc":3},{"edges":4,"entity":16,"fingerprint":44,"generatedAt":45,"neighbors":46,"schemaVersion":94},[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","951424:output:49534e44eb3e9feecd76cf40","https:\u002F\u002Fcordis.europa.eu\u002Fproject\u002Fid\u002F951424","exact","cordis:951424","edge:project-output:951424:49534e44eb3e9feecd76cf40","has_observed_output","output:49534e44eb3e9feecd76cf40",{"attributes":17,"edgeCount":27,"id":15,"indexable":28,"label":29,"links":30,"slug":39,"sourceRefs":40,"type":43},{"citationCount":18,"isOpenAccess":19,"openAireId":20,"outputType":21,"persistentIdentifiers":22,"publicationDate":26},0,false,"doi_dedup___::e3cad483d24571ee4710b6d28ec5d546","publication",[23],{"scheme":24,"value":25},"doi","10.1061\u002Fjwrmd5.wreng-6950","2025-10-01",1,true,"Usage of Multisource Data through Transfer Learning to Improve Short-Term Water Demand Forecasting",[31,35],{"kind":32,"label":33,"url":34},"official_source","OpenAIRE","https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3Ae3cad483d24571ee4710b6d28ec5d546",{"kind":36,"label":37,"url":38},"persistent_identifier","DOI 10.1061\u002Fjwrmd5.wreng-6950","https:\u002F\u002Fdoi.org\u002F10.1061\u002Fjwrmd5.wreng-6950","output-49534e44eb3e9feecd76cf40-4e1a25dc",[41],{"dataset":7,"field":42,"sourceId":20,"url":34},"openaire_research_product_id","output","sha256:6a0dc398239610a025a8fd0fb85cff78ff3ec23ed74237d0ee2a873b3c4edabb","2026-08-01T09:21:19.131Z",[47],{"attributes":48,"description":78,"edgeCount":79,"id":12,"indexable":28,"label":80,"links":81,"slug":88,"sourceRefs":89,"type":93},{"acronym":49,"code":50,"endDate":51,"frameworkProgramme":52,"funding":53,"knowledgeFlow":57,"research":65,"startDate":77},"Water-Futures","951424","2028-01-31","H2020",{"currency":54,"germanNetEuContributionCents":55,"participantEdgeCount":27,"status":56},"EUR","240625000","linked",{"citingCountryCount":58,"citingInstitutionCount":59,"distinctCitingWorkCount":60,"firstObservedCitationDate":61,"lastObservedCitationDate":62,"observedCitationEdgeCount":63,"status":64},90,1144,789,"1990-01-01","2026-07-30",985,"full_input_observation",{"citationDataOutputCount":66,"citedOutputCount":67,"firstPublicationDate":68,"lastPublicationDate":69,"openAccessOutputCount":70,"outputCount":66,"status":56,"totalCitations":71,"typeCounts":72},145,79,"2020-09-03","2026-05-01",122,663,{"dataset":73,"other":74,"publication":75,"software":76},3,4,124,14,"2021-08-01","Smart Water Futures: designing the next generation of urban drinking water systems",36,"Water-Futures · Smart Water Futures: designing the next generation of urban drinking water systems",[82,84],{"kind":32,"label":83,"url":10},"CORDIS",{"kind":85,"label":86,"url":87},"local_dossier","KI-Innovationspfad","\u002Ftools\u002Fki-innovationspfad\u002F?project=951424","project-cordis-951424-08764f38",[90],{"dataset":91,"field":92,"sourceId":12,"url":10},"german-ai-innovation-path","cordis_project_id","project","ki-evidenznetz.entity.v1",1785576540625]