[{"data":1,"prerenderedAt":259},["ShallowReactive",2],{"ki-evidenznetz-dossier-project-cordis-101168344-5f169c82":3},{"edges":4,"entity":54,"fingerprint":92,"generatedAt":93,"neighbors":94,"schemaVersion":258},[5,16,24,29,34,39,44,49],{"evidence":6,"evidenceClass":11,"from":12,"id":13,"relation":14,"to":15},{"dataset":7,"field":8,"sourceId":9,"url":10},"german-ai-innovation-path","cordis_project_code_and_participant_pic","cordis:101168344:participant:997336735","https:\u002F\u002Fcordis.europa.eu\u002Fproject\u002Fid\u002F101168344","exact","actor:cordis-pic:997336735","claim:funding:101168344:997336735","participates_in","cordis:101168344",{"evidence":17,"evidenceClass":11,"from":15,"id":21,"relation":22,"to":23},{"dataset":18,"field":19,"sourceId":20,"url":10},"german-ai-research-to-transfer-index","cordis_project_code","101168344:output:0182b811bee83301f80fd8f4","edge:project-output:101168344:0182b811bee83301f80fd8f4","has_observed_output","output:0182b811bee83301f80fd8f4",{"evidence":25,"evidenceClass":11,"from":15,"id":27,"relation":22,"to":28},{"dataset":18,"field":19,"sourceId":26,"url":10},"101168344:output:35c434ce4c230dcbb0111c2c","edge:project-output:101168344:35c434ce4c230dcbb0111c2c","output:35c434ce4c230dcbb0111c2c",{"evidence":30,"evidenceClass":11,"from":15,"id":32,"relation":22,"to":33},{"dataset":18,"field":19,"sourceId":31,"url":10},"101168344:output:85a1b3f1e0a6bc829777e0ef","edge:project-output:101168344:85a1b3f1e0a6bc829777e0ef","output:85a1b3f1e0a6bc829777e0ef",{"evidence":35,"evidenceClass":11,"from":15,"id":37,"relation":22,"to":38},{"dataset":18,"field":19,"sourceId":36,"url":10},"101168344:output:8fe5292816355a66731ca0fd","edge:project-output:101168344:8fe5292816355a66731ca0fd","output:8fe5292816355a66731ca0fd",{"evidence":40,"evidenceClass":11,"from":15,"id":42,"relation":22,"to":43},{"dataset":18,"field":19,"sourceId":41,"url":10},"101168344:output:e69c59bbf3412d3408c00424","edge:project-output:101168344:e69c59bbf3412d3408c00424","output:e69c59bbf3412d3408c00424",{"evidence":45,"evidenceClass":11,"from":15,"id":47,"relation":22,"to":48},{"dataset":18,"field":19,"sourceId":46,"url":10},"101168344:output:ec11593cf5816c86871b7b76","edge:project-output:101168344:ec11593cf5816c86871b7b76","output:ec11593cf5816c86871b7b76",{"evidence":50,"evidenceClass":11,"from":15,"id":52,"relation":22,"to":53},{"dataset":18,"field":19,"sourceId":51,"url":10},"101168344:output:f1b93dd0af13ae978cb158ef","edge:project-output:101168344:f1b93dd0af13ae978cb158ef","output:f1b93dd0af13ae978cb158ef",{"attributes":55,"description":75,"edgeCount":76,"id":15,"indexable":77,"label":78,"links":79,"slug":87,"sourceRefs":88,"type":91},{"acronym":56,"code":57,"endDate":58,"frameworkProgramme":59,"funding":60,"knowledgeFlow":62,"research":65,"startDate":74},"TUAI","101168344","2028-09-30","HORIZON",{"currency":61,"germanNetEuContributionCents":62,"participantEdgeCount":63,"status":64},"EUR",null,1,"participation_only",{"citationDataOutputCount":66,"citedOutputCount":67,"firstPublicationDate":68,"lastPublicationDate":69,"openAccessOutputCount":66,"outputCount":66,"status":70,"totalCitations":71,"typeCounts":72},7,5,"2024-01-01","2026-04-01","linked",26,{"dataset":73,"other":73,"publication":66,"software":73},0,"2024-10-01","Towards an Understanding of Artificial Intelligence via a transparent, open and explainable perspective",8,true,"TUAI · Towards an Understanding of Artificial Intelligence via a transparent, open and explainable perspective",[80,83],{"kind":81,"label":82,"url":10},"official_source","CORDIS",{"kind":84,"label":85,"url":86},"local_dossier","KI-Innovationspfad","\u002Ftools\u002Fki-innovationspfad\u002F?project=101168344","project-cordis-101168344-5f169c82",[89],{"dataset":7,"field":90,"sourceId":15,"url":10},"cordis_project_id","project","sha256:f5275a9a171842800cdf96142627427acb64fc183d3c4617fac3969e3ad08a44","2026-09-26T08:35:38.651Z",[95,116,142,160,180,197,220,236],{"attributes":96,"edgeCount":63,"id":12,"indexable":77,"label":98,"links":109,"slug":112,"sourceRefs":113,"type":115},{"aliases":97,"identifiers":99,"identityBasis":103,"kind":104,"lanes":105,"roles":107},[98],"AUMOVIO Microelectronic GmbH",[100],{"scheme":101,"value":102},"cordis-pic","997336735","official_identifier","organization",[106],"funding",[108],"funding_participant",[110],{"kind":111,"label":7,"url":10},"evidence_source","actor-cordis-pic-997336735-9559a786",[114],{"dataset":7,"field":103,"recordCount":63,"sourceId":9,"url":10},"actor",{"attributes":117,"edgeCount":63,"id":23,"indexable":77,"label":128,"links":129,"slug":137,"sourceRefs":138,"type":141},{"citationCount":73,"isOpenAccess":77,"openAireId":118,"outputType":119,"persistentIdentifiers":120,"publicationDate":127},"doi_dedup___::d19985f455a44e6e4f6b2a6d35625bbc","publication",[121,124],{"scheme":122,"value":123},"doi","10.1109\u002Ftnsre.2025.3645365",{"scheme":125,"value":126},"pmid","41406294","2026-01-01","Fall Monitoring With Single IMU: A Large-Scale Dataset and a Novel Dual-Branch Network",[130,133],{"kind":81,"label":131,"url":132},"OpenAIRE","https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3Ad19985f455a44e6e4f6b2a6d35625bbc",{"kind":134,"label":135,"url":136},"persistent_identifier","DOI 10.1109\u002Ftnsre.2025.3645365","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftnsre.2025.3645365","output-0182b811bee83301f80fd8f4-16e9237a",[139],{"dataset":18,"field":140,"sourceId":118,"url":132},"openaire_research_product_id","output",{"attributes":143,"edgeCount":63,"id":28,"indexable":77,"label":150,"links":151,"slug":157,"sourceRefs":158,"type":141},{"citationCount":144,"isOpenAccess":77,"openAireId":145,"outputType":119,"persistentIdentifiers":146,"publicationDate":149},17,"doi_dedup___::fae40af7b8abca90f5d46fd63771148b",[147],{"scheme":122,"value":148},"10.1007\u002Fs12559-025-10408-2","2025-02-17","Deep Learning Innovations in the Detection of Lung Cancer: Advances, Trends, and Open Challenges",[152,154],{"kind":81,"label":131,"url":153},"https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3Afae40af7b8abca90f5d46fd63771148b",{"kind":134,"label":155,"url":156},"DOI 10.1007\u002Fs12559-025-10408-2","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12559-025-10408-2","output-35c434ce4c230dcbb0111c2c-8e859185",[159],{"dataset":18,"field":140,"sourceId":145,"url":153},{"attributes":161,"edgeCount":63,"id":33,"indexable":77,"label":170,"links":171,"slug":177,"sourceRefs":178,"type":141},{"citationCount":162,"isOpenAccess":77,"openAireId":163,"outputType":119,"persistentIdentifiers":164,"publicationDate":68},2,"doi_dedup___::c0c7d72a25533027765230a7f917aa7f",[165,168],{"scheme":166,"value":167},"arXiv","2411.18472",{"scheme":122,"value":169},"10.48550\u002Farxiv.2411.18472","Isolating authorship from content with semantic embeddings and contrastive learning",[172,174],{"kind":81,"label":131,"url":173},"https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3Ac0c7d72a25533027765230a7f917aa7f",{"kind":134,"label":175,"url":176},"DOI 10.48550\u002Farxiv.2411.18472","https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2411.18472","output-85a1b3f1e0a6bc829777e0ef-44878524",[179],{"dataset":18,"field":140,"sourceId":163,"url":173},{"attributes":181,"edgeCount":63,"id":38,"indexable":77,"label":187,"links":188,"slug":194,"sourceRefs":195,"type":141},{"citationCount":67,"isOpenAccess":77,"openAireId":182,"outputType":119,"persistentIdentifiers":183,"publicationDate":186},"doi_dedup___::725265d2361e88dc3feeb6fc07ed21f1",[184],{"scheme":122,"value":185},"10.9781\u002Fijimai.2024.11.003","2024-12-01","Advances in AI-Generated Images and Videos.",[189,191],{"kind":81,"label":131,"url":190},"https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3A725265d2361e88dc3feeb6fc07ed21f1",{"kind":134,"label":192,"url":193},"DOI 10.9781\u002Fijimai.2024.11.003","https:\u002F\u002Fdoi.org\u002F10.9781\u002Fijimai.2024.11.003","output-8fe5292816355a66731ca0fd-ca9bc0ff",[196],{"dataset":18,"field":140,"sourceId":182,"url":190},{"attributes":198,"edgeCount":63,"id":43,"indexable":77,"label":207,"links":208,"slug":217,"sourceRefs":218,"type":141},{"citationCount":63,"isOpenAccess":77,"openAireId":199,"outputType":119,"persistentIdentifiers":200,"publicationDate":127},"doi_dedup___::281b40efa7f27e4b6f14fff34bbddf89",[201,203,205],{"scheme":166,"value":202},"2501.03940",{"scheme":122,"value":204},"10.1016\u002Fj.inffus.2025.103465",{"scheme":122,"value":206},"10.48550\u002Farxiv.2501.03940","Not all tokens are created equal: Perplexity Attention Weighted Networks for AI-generated text detection",[209,211,214],{"kind":81,"label":131,"url":210},"https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3A281b40efa7f27e4b6f14fff34bbddf89",{"kind":134,"label":212,"url":213},"DOI 10.1016\u002Fj.inffus.2025.103465","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.inffus.2025.103465",{"kind":134,"label":215,"url":216},"DOI 10.48550\u002Farxiv.2501.03940","https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2501.03940","output-e69c59bbf3412d3408c00424-2cf64a8f",[219],{"dataset":18,"field":140,"sourceId":199,"url":210},{"attributes":221,"edgeCount":63,"id":48,"indexable":77,"label":226,"links":227,"slug":233,"sourceRefs":234,"type":141},{"citationCount":73,"isOpenAccess":77,"openAireId":222,"outputType":119,"persistentIdentifiers":223,"publicationDate":69},"doi_________::66c082b5077af6a03806a87cc4ecaacf",[224],{"scheme":122,"value":225},"10.1109\u002Ftetci.2025.3645643","Discourse-Driven Detection of Multimodal Misinformation",[228,230],{"kind":81,"label":131,"url":229},"https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_________%3A%3A66c082b5077af6a03806a87cc4ecaacf",{"kind":134,"label":231,"url":232},"DOI 10.1109\u002Ftetci.2025.3645643","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftetci.2025.3645643","output-ec11593cf5816c86871b7b76-f03f6cc9",[235],{"dataset":18,"field":140,"sourceId":222,"url":229},{"attributes":237,"edgeCount":63,"id":53,"indexable":77,"label":245,"links":246,"slug":255,"sourceRefs":256,"type":141},{"citationCount":63,"isOpenAccess":77,"openAireId":238,"outputType":119,"persistentIdentifiers":239,"publicationDate":244},"doi_dedup___::eefca618bafe76f436c1489dc2dd5c0f",[240,242],{"scheme":122,"value":241},"10.1007\u002Fs12559-024-10394-x",{"scheme":122,"value":243},"10.21203\u002Frs.3.rs-5196699\u002Fv1","2024-12-04","On the Integration of Large-Scale Time Series Distance Matrices Into Deep Visual Analytic Tools",[247,249,252],{"kind":81,"label":131,"url":248},"https:\u002F\u002Fapi.openaire.eu\u002Fgraph\u002Fv3\u002Fresearch-products\u002Fdoi_dedup___%3A%3Aeefca618bafe76f436c1489dc2dd5c0f",{"kind":134,"label":250,"url":251},"DOI 10.1007\u002Fs12559-024-10394-x","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12559-024-10394-x",{"kind":134,"label":253,"url":254},"DOI 10.21203\u002Frs.3.rs-5196699\u002Fv1","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-5196699\u002Fv1","output-f1b93dd0af13ae978cb158ef-2254366b",[257],{"dataset":18,"field":140,"sourceId":238,"url":248},"ki-evidenznetz.entity.v1",1790412417327]