{"as_of":"2026-08-16T09:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:50db497ecb0dbc531340ef4dd8428e82e3da75023ae2d80c2c7e9ad14e7ffdff","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:51:01.822845Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/1908.08180/citation-record","integrity":"/paper/1908.08180/integrity","json":"/paper/1908.08180/citation-record.json","paper":"/paper/1908.08180"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:51:02.187073Z","title":null,"venue":null,"work_id":"82d5016e-e270-4a6c-af19-0f84ec735df5","year":2016},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.708457Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:1ba24e398a66d8ab6df21563febd732e99180e37d3c93497ff522913bbe646ec","observation_id":"e946b35d-e449-4ffa-b74f-ef179d0fb673","resolution":{"observed_at":"2026-08-14T11:51:02.190854Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.175874Z","title":null,"venue":null,"work_id":"5bf4ec6c-e5a3-4cb6-b026-11f9ec910893","year":2018},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.712847Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:44ea86901210a4909aeb2f43cbedf547088790843ab17c8d478685df748de2c3","observation_id":"7f185610-1242-45a4-b4d6-f6285b583826","resolution":{"observed_at":"2026-08-14T11:51:02.179607Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.164415Z","title":null,"venue":null,"work_id":"a8f46518-d151-40f0-9a1a-0f8301825a4f","year":2018},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.716914Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:0f23bdfe25da7d50ea50b00b3637fc89fe78a91c63769760d0c23791097224d7","observation_id":"8b8efe6a-330f-45b2-84e7-d918a3fc424d","resolution":{"observed_at":"2026-08-14T11:51:02.168900Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.152733Z","title":null,"venue":null,"work_id":"51262678-bc99-47c6-b771-14609216ea70","year":1998},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.721818Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:1ee90e770520dc9cb04c743fbc255c21605470828d4b8aea75e11b5dc6706e0d","observation_id":"b70fdd23-d7d1-4174-9e5a-5d503baa35a3","resolution":{"observed_at":"2026-08-14T11:51:02.156952Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.141199Z","title":null,"venue":null,"work_id":"50e7736f-2e96-4178-8fdf-41c4284dcc70","year":2008},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.725921Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:d259a7fa66ba163e2b35d7caac949e8ac58e3dc132a48527a0a0180666781563","observation_id":"5f59394f-6065-4c3a-b4dc-f8cf23778d4d","resolution":{"observed_at":"2026-08-14T11:51:02.144837Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.130034Z","title":"[Online]","venue":null,"work_id":"ddbb5fc7-f9b2-497c-aec8-1582e0b7e5e0","year":null},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.729959Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:7ab9fe36ead245f55ae94db01f9f03ce0f481d1377aeabd4ebdf3d88acd2ee13","observation_id":"a14087d0-7a91-4b97-a624-f2aafd839179","resolution":{"observed_at":"2026-08-14T11:51:02.133557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.118654Z","title":null,"venue":null,"work_id":"5a2f41d2-c2a1-4f2c-b41a-29a9c8bdbaac","year":null},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.733900Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:deff68f14b8d03e5478fa18b5f55987fb77e479cbb7fb69f1f22aa1ddf5228e6","observation_id":"913ceb5c-e2ff-4965-80a7-98253ef4c1b4","resolution":{"observed_at":"2026-08-14T11:51:02.122985Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.105039Z","title":"Zheng, B","venue":null,"work_id":"cbb0bf05-1fdd-4861-ad24-3a4a4f006952","year":2019},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.738068Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:b5ee754d99ca49c80e8add7c07b4320aceb8a7db9989a575e9af4206aa80793b","observation_id":"32c1992a-38ed-4f83-a670-11d580d0277b","resolution":{"observed_at":"2026-08-14T11:51:02.109046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.092984Z","title":"Ren and Y","venue":null,"work_id":"1dd01ba6-7d7b-4dc5-b019-ace8d84dc86d","year":2019},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.742143Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:698886291249a758fd8fd43b432f9957f99f484bfd0deee55d42459b09aca50f","observation_id":"3a25a42c-72f2-4c0d-bcf8-2715b764ee6b","resolution":{"observed_at":"2026-08-14T11:51:02.097107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05114","last_updated":"2019-01-16T02:34:11Z","snapshot_observed_at":"2026-08-14T17:30:25.928266Z","submitted_at":"2019-01-16T02:34:11Z","title":"Generative Adversarial Networks for Real-time Stability of Inverter-based Systems","version":1},"cited_work":{"arxiv_id":"1901.05114","doi":null,"metadata_source":"pith","pith_arxiv_id":"1901.05114","snapshot_observed_at":"2026-08-14T11:51:01.926895Z","title":"Generative Adversarial Networks for Real-time Stability of Inverter-based Systems","venue":"eess.SY","work_id":"83303981-bf5e-46ac-8aaf-1741d23381db","year":2019},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.745933Z"},"links":{"cited_paper":"/paper/1901.05114","citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:ababe5184ed48e633cd36755a2df99352ba2af452257700efa698f94a33db401","observation_id":"11cb9c7b-3025-47c2-b1dd-e59b2cb77f96","resolution":{"observed_at":"2026-08-14T11:51:01.931248Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.09527","last_updated":"2020-03-20T23:00:58Z","snapshot_observed_at":"2026-08-08T20:01:39.324588Z","submitted_at":"2020-03-20T23:00:58Z","title":"Predicting Real-Time Locational Marginal Prices: A GAN-Based Video Prediction Approach","version":1},"cited_work":{"arxiv_id":"2003.09527","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.09527","snapshot_observed_at":"2026-08-14T11:51:01.907837Z","title":"Predicting Real-Time Locational Marginal Prices: A GAN-Based Video Prediction Approach","venue":"cs.LG","work_id":"9d5e0950-6948-4324-a76e-eda43f5280bd","year":2020},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.750000Z"},"links":{"cited_paper":"/paper/2003.09527","citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:098c1261d1683ac3671161c2c3b7ef1ee686492e4ae7eb6b16c7ebd9fed37f8b","observation_id":"4ec2cd7b-1488-4810-a82e-eefa9ef7529a","resolution":{"observed_at":"2026-08-14T11:51:01.914084Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.081422Z","title":null,"venue":null,"work_id":"c4b8c1db-9bfc-4140-822d-111e5a7f22b9","year":2009},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.754645Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:f008911c1aabf74aece2922094d332708d174bc7becdd4ee4752efd2e9edd98b","observation_id":"30ad95fd-c985-4b33-87b7-dd46f982c432","resolution":{"observed_at":"2026-08-14T11:51:02.085241Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.068592Z","title":"Goodfellow, J","venue":null,"work_id":"39871f56-2b7f-4dce-8a94-69c9d7b6aa72","year":2014},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.758612Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:1213730256350bfe8cd75395d452973e701e6e4cfbc6a02368f9a34a9607adef","observation_id":"174ac1b8-a320-431c-9229-dbcebf2d9d5f","resolution":{"observed_at":"2026-08-14T11:51:02.074003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1701.07875","last_updated":"2017-12-06T20:01:54Z","snapshot_observed_at":"2026-08-14T21:19:18.245847Z","submitted_at":"2017-01-26T21:10:29Z","title":"Wasserstein GAN","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.07875","snapshot_observed_at":"2026-08-14T11:51:01.762653Z","title":"Arjovsky, S","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.762653Z"},"links":{"cited_paper":"/paper/1701.07875","citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:d6bec7aea007ee89792d4e1e81e6bd30cf5f6901ea3b621b55f660832207708c","observation_id":"c7fb6fd8-c76a-4ec1-bef1-0ce7cfdeef1e","resolution":{"observed_at":"2026-08-14T11:51:01.762653Z","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":"2026-08-14T11:51:02.057053Z","title":"Arjovsky, S","venue":null,"work_id":"aa738a20-173f-48c9-bb06-285ad0abcfec","year":2017},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.766784Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:74ce97d352983f41963cad912b4f16aa8f1f28116a402358e26d481669bc9c09","observation_id":"038f52f8-1932-4b1f-a34d-3414e7bb8308","resolution":{"observed_at":"2026-08-14T11:51:02.060782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.045586Z","title":"Gulrajani, F","venue":null,"work_id":"6934fd9a-3115-41d6-95c2-afc7a03a1ca7","year":2017},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.770755Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:bae2250ade0268668b1d678e40adeeac20c7139f8c746827e4b3c964e925011d","observation_id":"6f345374-26dd-4790-8be5-731b22aaba53","resolution":{"observed_at":"2026-08-14T11:51:02.049248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.033863Z","title":"Mescheder, G","venue":null,"work_id":"a70e03d4-e597-4fb0-acce-8e5a39d21202","year":2018},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.774674Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:054704fefc9293eed6345b55af790f01d6d52ff76ea42ded2dd6798a91c409d8","observation_id":"2c7cc419-2c07-4566-9154-b5e93a5ef9a7","resolution":{"observed_at":"2026-08-14T11:51:02.037904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.022312Z","title":null,"venue":null,"work_id":"90061b22-bb80-4463-b0d8-8189d2042b96","year":2019},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.779027Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:2be3514994bddc5dc7ae11e55fe09c78b8caf1ba6b92df45594e0119a4ce2c71","observation_id":"19838fa7-472f-4f0e-b2e2-1bfcacbb6468","resolution":{"observed_at":"2026-08-14T11:51:02.026506Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:02.011361Z","title":null,"venue":null,"work_id":"dfa87133-1167-406b-9efe-a1c567a9dbb1","year":2017},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.783059Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:5a09d46e9d51f6e10c769ea1364add9981ae2140e1901ecd958560f783411bd9","observation_id":"bcf88e6b-8537-4d15-9794-918df18d83f8","resolution":{"observed_at":"2026-08-14T11:51:02.014950Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.10847","last_updated":"2017-07-18T08:07:36Z","snapshot_observed_at":"2026-08-14T21:08:57.546222Z","submitted_at":"2017-03-31T10:59:58Z","title":"MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.10847","snapshot_observed_at":"2026-08-14T11:51:01.786571Z","title":"Y ang, S","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.786571Z"},"links":{"cited_paper":"/paper/1703.10847","citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:e19fb27aad12021279778541e9e0cc0f69ac603ecc641f280030a3a0013f1920","observation_id":"453208a4-5894-4cff-876c-988d6335ef58","resolution":{"observed_at":"2026-08-14T11:51:01.786571Z","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":"2026-08-14T11:51:01.998139Z","title":null,"venue":null,"work_id":"94bf5b01-4cf2-4ac7-b976-385a14c09210","year":2017},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.790677Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:09688991a9963bceafef3c6a7d97a04e075c2f1a1638c297d4cbe9ba6db79ea4","observation_id":"0a68cd12-e901-4e9f-8d8b-1e6ad8d589ba","resolution":{"observed_at":"2026-08-14T11:51:02.002723Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.11419","last_updated":"2019-04-25T15:49:23Z","snapshot_observed_at":"2026-08-15T00:23:53.244433Z","submitted_at":"2019-04-25T15:49:23Z","title":"Time Series Simulation by Conditional Generative Adversarial Net","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.11419","snapshot_observed_at":"2026-08-14T11:51:01.794944Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.794944Z"},"links":{"cited_paper":"/paper/1904.11419","citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:88cf5f9553400a54345b17ecbdcc5b7b59ad3e46192c918607b042b8c535ddba","observation_id":"b5b14b54-590f-45bc-9c38-8e82a720e037","resolution":{"observed_at":"2026-08-14T11:51:01.794944Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.13403","last_updated":"2021-01-17T04:54:51Z","snapshot_observed_at":"2026-08-12T22:39:58.742391Z","submitted_at":"2019-09-30T00:13:19Z","title":"Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.13403","snapshot_observed_at":"2026-08-14T11:51:01.799336Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.799336Z"},"links":{"cited_paper":"/paper/1909.13403","citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:3c2c182b5d8b13a591a6d6dc497033c5e27a0c48b5c156213e7f81f65b895a10","observation_id":"3454a22c-9113-4427-991e-da77920e63d3","resolution":{"observed_at":"2026-08-14T11:51:01.799336Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.06434","last_updated":"2016-01-07T23:09:39Z","snapshot_observed_at":"2026-08-12T18:43:14.431633Z","submitted_at":"2015-11-19T22:50:32Z","title":"Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.06434","snapshot_observed_at":"2026-08-14T11:51:01.803188Z","title":"Radford, L","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.803188Z"},"links":{"cited_paper":"/paper/1511.06434","citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:3270f138423f1ad01ffc600a0f7b64d9244beeb36f6dda46845a7938e4907a3f","observation_id":"d231ecdc-2cd3-469c-976d-a575ae0df9bd","resolution":{"observed_at":"2026-08-14T11:51:01.803188Z","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":"2026-08-14T11:51:01.985964Z","title":"Pai and J","venue":null,"work_id":"9c951c18-3209-462d-9eb1-0bf01e2f66fd","year":2017},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.807217Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:8e7c78b9714dc4d0b6a584ced103db475ffa471cba36017f29ead08b430be3e7","observation_id":"4a6866d8-469f-4067-895b-3170286560bc","resolution":{"observed_at":"2026-08-14T11:51:01.990053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:01.972911Z","title":"”Identification of electromechanical modes in power systems.” IEEE Task Force Report, 2012","venue":null,"work_id":"863bf388-792b-4664-a21a-c459eb1392a9","year":2012},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.811013Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:de60ffea2406ba92d5306f3c1bd4a0be6257b888a5d5d8864a79f65e813beeae","observation_id":"f7dc9177-e4d7-4b21-b69b-3fc83e3a96cf","resolution":{"observed_at":"2026-08-14T11:51:01.977216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:01.961853Z","title":"Kundur, N","venue":null,"work_id":"c380a999-bfca-43e6-ac98-8943b005f1fb","year":1994},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.814911Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:a7fe3615f58ac6cf403d9001b02846b2dfe09eb5770a18611bff28a8401913e4","observation_id":"7ad5c6cf-0719-42c8-bb17-228a7db497d0","resolution":{"observed_at":"2026-08-14T11:51:01.965276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:01.951115Z","title":null,"venue":null,"work_id":"71907f44-80e0-4a1e-8c00-53c44625f4ed","year":null},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.818887Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:3ff11684b230219d78e1eb1d132b09d17ae0eba77d64c7c79415ba81c7e174a4","observation_id":"8cbcde11-9138-4af2-8664-c626e647fec2","resolution":{"observed_at":"2026-08-14T11:51:01.954753Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:51:01.939235Z","title":"Cai and Y","venue":null,"work_id":"186c1c32-7721-4318-afdd-fe8cc743fc56","year":null},"citing_paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T11:51:01.822845Z"},"links":{"citing_paper":"/paper/1908.08180"},"observation_digest":"sha256:2e43a2c79b37baf277bebaf0930090f30d9e643f1e42cbbe8afa074e018dae1b","observation_id":"40a91974-3f54-4a0c-9113-58ad594eb210","resolution":{"observed_at":"2026-08-14T11:51:01.942988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.08180","last_updated":"2020-04-07T01:46:45Z","latest_version":2,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-15T13:30:21.497709Z","submitted_at":"2019-08-22T03:25:51Z","title":"Creation of Synthetic Networked PMU Data: A Generative Adversarial Network Approach"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":2,"verified_fuzzy":11},"total_outbound_references":29},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:1908.08180."}