{"as_of":"2026-08-20T00:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f7a218a81243f083dc23011f4b30974ca388aa7b90cb35f6b13c9a64d763a2ef","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T05:49:02.024730Z","state":"measured"},{"denominator":44,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":44,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.01278/citation-record","integrity":"/paper/2508.01278/integrity","json":"/paper/2508.01278/citation-record.json","paper":"/paper/2508.01278"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:03.496505Z","title":"Graph neural networks in recommender systems: A survey,","venue":null,"work_id":"f6f3b4e5-45dd-4540-8872-f2356dafcad3","year":2022},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:58.414939Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:6f4214906fb3008848e20649fde5706dcb92bd8b42154ae4ce4f64cf0174f8a0","observation_id":"d51b2dcc-82d3-4713-97ae-f8d95539d356","resolution":{"observed_at":"2026-08-06T05:49:03.504802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:03.471778Z","title":"A novel method for analog fault diagnosis based on neural networks and genetic algorithms,","venue":null,"work_id":"aa3381c0-3274-4927-9546-827a24f2ea38","year":2008},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:58.479981Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:5c665bdfecb732750a5de855772f94bf5afafa49673b170e2fec6072f53d8777","observation_id":"a8603bac-54a5-4594-ab5e-41170d1700b6","resolution":{"observed_at":"2026-08-06T05:49:03.480974Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:03.444577Z","title":"Table structure recognition and form parsing by end-to-end object detection and relation parsing,","venue":null,"work_id":"d401df09-e84a-4afc-86b4-e16693460422","year":2022},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:58.582679Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:18357130d11823e7dd1dd05b90d50f32815046f326309ab6d93223c6ffd30690","observation_id":"903bf6c7-e276-4988-a999-a7a50c996151","resolution":{"observed_at":"2026-08-06T05:49:03.454077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:03.408070Z","title":"Identifying spreading influence nodes for social networks,","venue":null,"work_id":"4999688b-63f7-416d-aaff-64e9a89e0e43","year":2022},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:58.678711Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:a25f24787b18f52304d399291dd088f71607abb01c6c6abc8d284701fb18b877","observation_id":"f53daf8d-10ee-4a91-ab05-8f99c2706e93","resolution":{"observed_at":"2026-08-06T05:49:03.417125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:03.268981Z","title":"Identifying critical nodes in complex networks via graph convolutional networks,","venue":null,"work_id":"848e5d2f-d2c2-464c-961e-fb401e3b3678","year":2020},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:58.784871Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:e04fbeed4da696c0f5b3e626cd17f390fc62d0a038306d089108f472c1bbf178","observation_id":"3f5b9c95-b97d-49bf-aaf9-58f7809dec4d","resolution":{"observed_at":"2026-08-06T05:49:03.334592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:03.125288Z","title":"Infgcn: Identifying influential nodes in complex networks with graph convolutional networks,","venue":null,"work_id":"c0f7d072-91cf-47b7-aa04-2828180928be","year":2020},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:58.858537Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:54a68acf37853c07c989aed19a1b0d80edc2fcb7e0e81b244bf19dffc7ee120c","observation_id":"9a69a882-2101-4440-bfe9-d60f9783ae0a","resolution":{"observed_at":"2026-08-06T05:49:03.178106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.997722Z","title":"A new approach for evaluating node importance in complex networks via deep learning methods,","venue":null,"work_id":"f8effeb6-2d06-4a2a-a210-04b60e51f3b3","year":2022},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:58.941937Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:82ebc620c4f2d315c26e0e3e22a638f5d1162ff0ef5db0864c59df59e0b092fa","observation_id":"1643bbb6-c05b-44cb-988f-bb233921245b","resolution":{"observed_at":"2026-08-06T05:49:03.043296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.955599Z","title":"Centrality indices,","venue":null,"work_id":"7e71a0c0-84f9-4091-9f64-fe8f14d4d9aa","year":2005},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.013675Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:f47f1721977059e26b2b7293c2e2795081ebb9871af0ea3892251e93491bca47","observation_id":"51615ac2-591d-420d-86ed-a8f3f8220475","resolution":{"observed_at":"2026-08-06T05:49:02.961739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.938584Z","title":"A model of internet topology using ¡i¿k¡/i¿-shell decomposition,","venue":null,"work_id":"50522b8d-97fa-42c4-813e-2021eeb2450d","year":2007},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.081233Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:5e0563df5979d4c80825a3fd6721091f48f6427da4bdec62e5825720f4034e73","observation_id":"1fee61ef-0b5c-4bc2-b0aa-12f93c49b231","resolution":{"observed_at":"2026-08-06T05:49:02.944031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.914273Z","title":"Support vector machines,","venue":null,"work_id":"6571d0ff-5f8f-445b-a1f6-6b9ce28f3165","year":1998},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.164272Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:f33223c19e761e9fdf5ea91f7abb31b96f838214e7d89f1f38da4cf3d65ae6c2","observation_id":"242ad72b-3386-4a4f-ac66-86e19c5c3ad6","resolution":{"observed_at":"2026-08-06T05:49:02.919944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.888393Z","title":"Logistic regression,","venue":null,"work_id":"6a28f388-0e97-4776-9fff-5e57448e8ee4","year":2008},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.248652Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:923fdf9f1dcb4ad6839f985843efe64bb9b61b2286f8954257f1e326fdba237c","observation_id":"810d015a-058a-4fe7-adab-b81e9f5e927d","resolution":{"observed_at":"2026-08-06T05:49:02.893824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.869234Z","title":"Graph neural networks: A review of methods and applications,","venue":null,"work_id":"09f68451-a3fe-41a7-8b62-edf029741230","year":2020},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.294571Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:bb74344ac3401487c527e7376127d94b2027b7e0b6a1a0d0c8de101bb765f075","observation_id":"638cccf5-0b33-47e3-a3e4-b0e82159e3e2","resolution":{"observed_at":"2026-08-06T05:49:02.874676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.845753Z","title":"Simple and deep graph convolutional networks,","venue":null,"work_id":"9d5e9896-71f9-4246-b85c-04b48dbce5dc","year":2020},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.326551Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:d8a5963730bdc11bf397285c6dffb7230d4ee6114ccf4008f58c22e2d0fa4711","observation_id":"23df52aa-59d7-41ea-a8dc-0c77722380b8","resolution":{"observed_at":"2026-08-06T05:49:02.853431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-08-17T10:49:36.026134Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-06T05:48:59.345658Z","title":"Semi-supervised classification with graph convolutional networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.345658Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:b0d53c8bd8e8b75ad56261c7db91f7fe39fbcb8cf665eb0ba235e4d7681987a2","observation_id":"59a1b3b4-10ba-4cb4-8788-5b1c2f46cc6a","resolution":{"observed_at":"2026-08-06T05:48:59.345658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.823042Z","title":"Mathematical modeling of diseases: Susceptible-infected-recovered (sir) model,","venue":null,"work_id":"7d521cdc-a9b1-4bb5-aa17-873f0a95e7f6","year":2009},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.446252Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:d568da001e5f877653f93cda26283a979f67299b4b6da6c0ae6e848708a1ae6e","observation_id":"35ab61f8-4667-4666-8733-6567f6f24d95","resolution":{"observed_at":"2026-08-06T05:49:02.831140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.802170Z","title":"Ranking of closeness centrality for large-scale social networks,","venue":null,"work_id":"b4ce0d61-b3df-42dc-b6a6-59303bd24b88","year":2008},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.586585Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:7378c5fa5a17a950d33e76c3f5b2af0ca1fc7a3a60e2325237f49105e5d3b5d6","observation_id":"c7f6c204-4adf-4d2a-ad7c-e70e6e19901b","resolution":{"observed_at":"2026-08-06T05:49:02.809181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.784003Z","title":"Betweenness centrality in large complex networks,","venue":null,"work_id":"839977bc-db98-46cc-b706-836f420470fa","year":2004},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.694921Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:4e08e496fe6f8b26775da21a461a45d6c219e793aee43fa3e921874ef85971e6","observation_id":"866af2ba-0c20-45ab-a0be-2dd30c71af1f","resolution":{"observed_at":"2026-08-06T05:49:02.790036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.766080Z","title":null,"venue":null,"work_id":"a22a5745-d21b-43b3-8a12-b8f9c180fc74","year":2006},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.821784Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:32734644ee937b23e9112f79c1400b43972a7456f1e397ca4d7567427f45ddaf","observation_id":"ce836e6d-31af-496b-8aac-760426e57152","resolution":{"observed_at":"2026-08-06T05:49:02.772062Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.745214Z","title":"Eigenvector-centrality—a node-centrality?","venue":null,"work_id":"01e8a09f-922e-42d9-9c41-4519e3342689","year":2000},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:59.913970Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:10e417fe102f7ad6538303bbb491194f2594b54668116110aafeb3ae22beaf6f","observation_id":"f76b38d9-4dd1-48bf-8cdf-df4986f07b90","resolution":{"observed_at":"2026-08-06T05:49:02.751869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.726755Z","title":"Graph convolutional networks: a comprehensive review,","venue":null,"work_id":"7ad014a8-6d7c-4860-a3d6-7eb9ed72a337","year":2019},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.058643Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:ee9215d113faa11afaddaa15cd7585ea13b14fe7b2b19babb1bc8c75c62fea4f","observation_id":"df3d47d8-3ea1-419c-9c5a-88f082fcdbbf","resolution":{"observed_at":"2026-08-06T05:49:02.732117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.706638Z","title":"Fg-rs: Capture user fine-grained preferences through attribute information for recommender systems,","venue":null,"work_id":"48479ff5-f011-4466-9a6c-bd3755ecce60","year":2021},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.178308Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:8caccf91cd0a42384427972bbcd924e140f78504bbb9c89561c833ecfb641123","observation_id":"90062f24-8b3e-42b0-8df6-b31fd0686b40","resolution":{"observed_at":"2026-08-06T05:49:02.711915Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.684661Z","title":"Differential evolution based on network structure for feature selection,","venue":null,"work_id":"7b9afde4-5734-4ddd-96d2-7203f32b1b37","year":2023},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.243848Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:42ed8284ea97ca177d149253d4ff5ad2d4dd0611570d03659f209d16f7094251","observation_id":"32ab230c-7af5-456f-8721-e0abef14110c","resolution":{"observed_at":"2026-08-06T05:49:02.691148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.662768Z","title":"A multi-level damage classification technique of aircraft plate structures using lamb wave- based deep transfer learning network,","venue":null,"work_id":"68f8f7f0-9b57-4970-89d0-c26f14c85b0f","year":2022},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.251553Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:4ec2c9c4dada06b2d86072304ea7bb9c4eb7061a9a37f78762f66d4e75f60a14","observation_id":"855cad10-a9a6-42ed-865d-b41245bbfa06","resolution":{"observed_at":"2026-08-06T05:49:02.670507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.638101Z","title":"A novel flexible sensor for double- parameter decoupling measurement of temperature and pressure with high sensitivity and wide range,","venue":null,"work_id":"f626170a-c1a4-48ec-a16c-9187fa6c46df","year":2023},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.293436Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:4432f84cc1b711aaba327654bd81a24914e427d6ab5c99a1339a7257c48b25f9","observation_id":"b3b3a386-de2e-4c44-a589-7357342d8593","resolution":{"observed_at":"2026-08-06T05:49:02.645969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.08795","last_updated":"2019-11-20T10:02:19Z","snapshot_observed_at":"2026-08-19T11:24:38.858504Z","submitted_at":"2019-11-20T10:02:19Z","title":"On Node Features for Graph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.08795","snapshot_observed_at":"2026-08-06T05:49:00.394092Z","title":"On node features for graph neural networks,","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.394092Z"},"links":{"cited_paper":"/paper/1911.08795","citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:2d6b2ad4a2750a45f02e5c92cf9a7b52134f0d550d43d8c90f394680cf1d234f","observation_id":"1c82bab7-2387-42d0-8801-4ad9cad1e7f1","resolution":{"observed_at":"2026-08-06T05:49:00.394092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.616164Z","title":"Comparative analysis of centrality measures for identifying critical nodes in complex networks,","venue":null,"work_id":"2e46c91b-a620-4cc7-9ff7-3cf8cca5a468","year":2022},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.473239Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:50de5dae475acf7de3839f0c6a895a884ffa5adc9e5dade7243e7d71fd0ca0de","observation_id":"5d765d6e-3e9f-456c-a33e-99b66c0c12c0","resolution":{"observed_at":"2026-08-06T05:49:02.623603Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.594890Z","title":"Ranking nodes in complex networks based on local structure and improving closeness centrality,","venue":null,"work_id":"cafc5a3a-2ae0-46b0-8f19-965de4d5f974","year":2019},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.548301Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:af0f6aa9e5bb1d4a72aea97812d02459419af7b505e1e41499be4fc12df2f572","observation_id":"b865d1e0-e026-428d-8bf3-8bcc9bd0b212","resolution":{"observed_at":"2026-08-06T05:49:02.602048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.574271Z","title":"Acquiring academic literacy: a case of first-year extended degree programme students,","venue":null,"work_id":"e0fedcfe-d91a-4c37-ba46-5a89872b1cc1","year":2010},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.606699Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:241df94a103f1c6a99569523b0464e1686149d8081e62f19452ecdb047d86668","observation_id":"625d55b0-4c18-4c3d-aa9c-3597ffd40c97","resolution":{"observed_at":"2026-08-06T05:49:02.581379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.550708Z","title":"Using accumulated degree-days to estimate the postmortem interval from decomposed human remains,","venue":null,"work_id":"018f1a50-6fdf-4bea-9ee5-4fee402bf9ee","year":2005},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.662092Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:b532ebdd69fb717d19230099a353f00f3a192e0d8d22f3373faaa33a68e53c6e","observation_id":"f570b2dc-45ce-41b3-9562-4b54f4921345","resolution":{"observed_at":"2026-08-06T05:49:02.558499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.526028Z","title":"A robust two-stage algorithm for local community detection,","venue":null,"work_id":"bd419705-9182-40ff-aacb-f5209048440f","year":2018},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.746299Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:bd4a7ec6aff11ba5ad39d19bcb27c907126211404f15a9babbd3fc91af0bcba7","observation_id":"7dd3bb06-fe29-415e-8731-b2073d7b242b","resolution":{"observed_at":"2026-08-06T05:49:02.532800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.506085Z","title":"Overlapping community detection using neighborhood-inflated seed expansion,","venue":null,"work_id":"be693eea-3e3d-4ce2-bc99-8d189737dd16","year":2016},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.815053Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:dcbbdc7ec93daf09f00144ddba415f620f97ef67514e345ee3ec25d471309b3a","observation_id":"722d4ebc-5add-4df9-a99a-c19f19342f86","resolution":{"observed_at":"2026-08-06T05:49:02.512437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.485694Z","title":"Local clustering coeffi- cient in generalized preferential attachment models,","venue":null,"work_id":"a9b8cda7-3776-468f-ac78-43e80ac55c7a","year":2015},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.927792Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:93678a2114abf18a8a418871aa7d43ae68bd2d33b250b092f77056660cc8a2ee","observation_id":"f28ef2c0-43b8-4193-901e-ca57eb7863d0","resolution":{"observed_at":"2026-08-06T05:49:02.494229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.457457Z","title":"Community detection in complex networks by detecting and expanding core nodes through ex- tended local similarity of nodes,","venue":null,"work_id":"d16adcaa-7d28-4c64-bd70-ff70e024c02a","year":2018},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:00.974600Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:e7f0a25253515720f2bac6c921953be9452cb85434582e79ec9edafa0e7e6036","observation_id":"98f690c9-506e-4aba-ab5c-a01a3cf6811f","resolution":{"observed_at":"2026-08-06T05:49:02.470377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.411382Z","title":"Node classification with graph neural network based centrality measures and feature selection,","venue":null,"work_id":"7ca5b4fb-811b-4386-af93-e84f94f2878d","year":2023},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.096303Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:da93f667965db674c145f9df1423db8969cddca0d6a4526313fa890e1f2f14b4","observation_id":"6b8b80b3-edb1-4970-b0b5-221c194fe78b","resolution":{"observed_at":"2026-08-06T05:49:02.425113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.377839Z","title":"Spearman correlation coefficients, differ- ences between,","venue":null,"work_id":"581a32d9-0d29-436d-ab07-9894d2d0a41c","year":2004},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.204023Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:0bd4aad96356b233da0339feb3e289d6323482c7e920d05d0a866650d3b021d3","observation_id":"b63046ea-77a3-4eeb-9197-0eb1efdb5648","resolution":{"observed_at":"2026-08-06T05:49:02.390273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.343661Z","title":"Similarity detection method of science fiction painting based on multi-strategy improved sparrow search algorithm and gaussian pyramid,","venue":null,"work_id":"df480959-d9aa-4354-b1c8-a1c676e1ad77","year":2023},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.279403Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:5ad4fab81e4b47d574996204b5574f1fbb10748bedaeb61b8f3339a3ddae2478","observation_id":"b2e52285-e35c-49c8-9206-d5c0e808ff3c","resolution":{"observed_at":"2026-08-06T05:49:02.351227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.303551Z","title":"A sir model assumption for the spread of covid-19 in different communities,","venue":null,"work_id":"1b3b3292-0a50-46e2-b1fe-a15e7b16db86","year":2020},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.390959Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:6c2e78e150c45c98c2afcfadf04cededfbfe886e2add9bd765701c72f93f1c04","observation_id":"31543e44-4680-44a7-9692-15a27e0e3a35","resolution":{"observed_at":"2026-08-06T05:49:02.309970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.284529Z","title":"Sir-im: Sir rumor spreading model with influence mechanism in social networks,","venue":null,"work_id":"8e8371c0-eec9-4d7d-a0e2-f3e8ba18275b","year":2021},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.483752Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:822d5ce556debebd865c3bc4259e8f182947c4264bb310d23ed6e3bb6bd21643","observation_id":"ebd828ab-788b-4bf5-9a98-06370f61c331","resolution":{"observed_at":"2026-08-06T05:49:02.290930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.261321Z","title":null,"venue":null,"work_id":"a1e6a508-8de4-415f-8bfb-5a5c19e36a6d","year":2017},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.600460Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:02e71e7570a21e19c793e056f3f427519f6856d731479822b01620b3bb9176c7","observation_id":"ee46c9e6-1204-4410-b41f-7ec7337f45eb","resolution":{"observed_at":"2026-08-06T05:49:02.269833Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.240321Z","title":"Graph evolution: Den- sification and shrinking diameters,","venue":null,"work_id":"d123e546-3dcb-4401-9d86-7f252b092faf","year":2007},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.719895Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:4edb3eae740c8314dea6a0bc32308a0432e3c8b5426131d82805e46b686cc047","observation_id":"44b79753-c9c6-492d-812f-4206c53567f8","resolution":{"observed_at":"2026-08-06T05:49:02.248104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-06T05:49:01.832768Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.832768Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:c387e100721250d9c4eba8676b8b19cb299a4d13e17750acc3810a339864a5bf","observation_id":"20d974b3-d73c-4b82-87ea-7fe53986a7be","resolution":{"observed_at":"2026-08-06T05:49:01.832768Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.217342Z","title":"Thresholding classifiers to maximize f1 score,","venue":null,"work_id":"677f52ab-b328-45cc-8872-c467c358b007","year":2014},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.911169Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:f967681ee8b03dc18bbb2c1aa3f40a968af5237fe04473545594f0350c6a8d49","observation_id":"0a970c7c-a712-4c44-acd4-f54d4e349fb5","resolution":{"observed_at":"2026-08-06T05:49:02.222891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:01.966666Z","title":"The use of the area under the roc curve in the evaluation of machine learning algorithms,","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:01.966666Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:f58fd121430d8e22a0ff115e8c685f696a3479ff6ccb6b9fb36450a62f045a8e","observation_id":"a8b45c65-d9aa-4613-9e1f-ed58752170cb","resolution":{"observed_at":"2026-08-06T05:49:01.966666Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T05:49:02.166008Z","title":"How attentive are graph attention networks?","venue":null,"work_id":"e0d7d1fb-ce8e-4d80-bdb9-23fb5d1242d3","year":2022},"citing_paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T05:49:02.024730Z"},"links":{"citing_paper":"/paper/2508.01278"},"observation_digest":"sha256:12eb66149a9eb67479a8ceb81e6349dc642f15875bc62d7ed714479ee4afc59d","observation_id":"ba6ed581-dd78-4c65-a9ae-e0320c2589cc","resolution":{"observed_at":"2026-08-06T05:49:02.176622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.01278","last_updated":"2025-08-02T09:15:52Z","latest_version":1,"primary_category":"cs.SI","snapshot_observed_at":"2026-08-13T05:24:09.797981Z","submitted_at":"2025-08-02T09:15:52Z","title":"A graph neural network based on feature network for identifying influential nodes"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":38},"total_outbound_references":44},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2508.01278."}