[{"data":1,"prerenderedAt":104},["ShallowReactive",2],{"ki-evidenznetz-dossier-output-81b46c2fcbf3dfb5aa3e1289-f9a3fe2a":3},{"edges":4,"entity":16,"fingerprint":54,"generatedAt":55,"neighbors":56,"schemaVersion":103},[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","101058625:output:81b46c2fcbf3dfb5aa3e1289","https:\u002F\u002Fcordis.europa.eu\u002Fproject\u002Fid\u002F101058625","exact","cordis:101058625","edge:project-output:101058625:81b46c2fcbf3dfb5aa3e1289","has_observed_output","output:81b46c2fcbf3dfb5aa3e1289",{"attributes":17,"edgeCount":35,"id":15,"indexable":19,"label":36,"links":37,"slug":49,"sourceRefs":50,"type":53},{"citationCount":18,"isOpenAccess":19,"openAireId":20,"outputType":21,"persistentIdentifiers":22,"publicationDate":34},2,true,"doi_dedup___::35ef6ba358be3d1d313e161040a4c444","publication",[23,26,29,31],{"scheme":24,"value":25},"arXiv","2503.02749",{"scheme":27,"value":28},"doi","10.1016\u002Fj.ecoinf.2025.103368",{"scheme":27,"value":30},"10.48550\u002Farxiv.2503.02749",{"scheme":32,"value":33},"handle","11572\u002F473771","2025-11-01",1,"Improving oil slick trajectory simulations with Bayesian optimization",[38,42,46],{"kind":39,"label":40,"url":41},"official_source","OpenAIRE","https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3A35ef6ba358be3d1d313e161040a4c444",{"kind":43,"label":44,"url":45},"persistent_identifier","DOI 10.1016\u002Fj.ecoinf.2025.103368","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ecoinf.2025.103368",{"kind":43,"label":47,"url":48},"DOI 10.48550\u002Farxiv.2503.02749","https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2503.02749","output-81b46c2fcbf3dfb5aa3e1289-f9a3fe2a",[51],{"dataset":7,"field":52,"sourceId":20,"url":41},"openaire_research_product_id","output","sha256:59e12ca2524b6e1720e62555338cd1044eb298dada1e7e4bbb6ee5f59a887f38","2026-08-01T09:21:19.131Z",[57],{"attributes":58,"description":87,"edgeCount":88,"id":12,"indexable":19,"label":89,"links":90,"slug":97,"sourceRefs":98,"type":102},{"acronym":59,"code":60,"endDate":61,"frameworkProgramme":62,"funding":63,"knowledgeFlow":67,"research":75,"startDate":86},"iMagine","101058625","2025-08-31","HORIZON",{"currency":64,"germanNetEuContributionCents":65,"participantEdgeCount":18,"status":66},"EUR","45718750","linked",{"citingCountryCount":68,"citingInstitutionCount":69,"distinctCitingWorkCount":70,"firstObservedCitationDate":71,"lastObservedCitationDate":72,"observedCitationEdgeCount":73,"status":74},44,230,82,"2023-01-01","2026-07-12",94,"full_input_observation",{"citationDataOutputCount":76,"citedOutputCount":77,"firstPublicationDate":78,"lastPublicationDate":79,"openAccessOutputCount":80,"outputCount":76,"status":66,"totalCitations":81,"typeCounts":82},128,28,"2022-01-01","2025-12-15",124,91,{"dataset":83,"other":84,"publication":73,"software":85},27,7,0,"2022-09-01","Imaging data and services for aquatic science",26,"iMagine · Imaging data and services for aquatic science",[91,93],{"kind":39,"label":92,"url":10},"CORDIS",{"kind":94,"label":95,"url":96},"local_dossier","KI-Innovationspfad","\u002Ftools\u002Fki-innovationspfad\u002F?project=101058625","project-cordis-101058625-4ab9878a",[99],{"dataset":100,"field":101,"sourceId":12,"url":10},"german-ai-innovation-path","cordis_project_id","project","ki-evidenznetz.entity.v1",1785576531702]