{"as_of":"2026-08-23T09:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:276f545c362ea08d96305d000d7463afc9bc3c6580d00dd42022c5c8e071120e","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T18:34:44.348654Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2411.11497/citation-record","integrity":"/paper/2411.11497/integrity","json":"/paper/2411.11497/citation-record.json","paper":"/paper/2411.11497"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.214719Z","title":"Nature Computational Science 1, 166–168 (2021) https://doi.org/10.1038/s43588-021-00040-z","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.214719Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:7fa15d24028fe698da2e4fbef1a64dae044be9bfc9843d2a54c454830ad495fd","observation_id":"b0083b5f-0a70-4891-8079-af50391f84e8","resolution":{"observed_at":"2026-08-12T18:34:44.214719Z","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":"10.1016/j.jmsy.2022","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.414062Z","title":"Journal of Manufacturing Systems63, 381–391 (2022) https://doi.org/10.1016/j.jmsy.2022","venue":null,"work_id":"88a33948-3e8a-4c87-9e17-7870ae0d793d","year":2022},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.218366Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:53e7d90c44499ae32036c586106223953498b6af0e6a48dcf7a37ae7627bc99f","observation_id":"4ee85288-a942-4820-bd40-4d4e831068f0","resolution":{"observed_at":"2026-08-12T18:34:44.417188Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2020.29701","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.543127Z","title":"IEEE Access8, 21980–22012 (2020) https://doi","venue":null,"work_id":"90d44b75-b2e2-4f3d-8cfb-26286f5a6555","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.221673Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:9c527a5084a708598983354b83f1fe74ca92bc375c7e8fd6e8fa9078e85ea04a","observation_id":"30251cbf-bc9a-4564-9c84-9be3ddb072b2","resolution":{"observed_at":"2026-08-12T18:34:44.548255Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.823178Z","title":"Structural and Multidisciplinary Optimization65, 354 (2022) https://doi.org/10.1007/ s00158-022-03425-4","venue":null,"work_id":"0eb1ef0f-9af4-4d69-bafa-973d83654996","year":2022},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.224658Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:359c349db72e548a5f4e325b29a1d52178df05202e61d67fb1f1d74292d889ff","observation_id":"8e5fa064-05c1-49f4-bd10-ae282b0eebb8","resolution":{"observed_at":"2026-08-12T18:34:44.826085Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.814964Z","title":"Nature Machine Intelligence3, 218–229 (2021)","venue":null,"work_id":"14e113bf-eba2-4638-a92c-b053f680cef4","year":2021},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.228014Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:25edef9fc87baab0648c392dc1d8e40ea94fea39e84ef366a84afbdae325eb4c","observation_id":"80284310-7909-4477-b75e-6a670cb9f193","resolution":{"observed_at":"2026-08-12T18:34:44.817823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.806791Z","title":"Journal of Computational Physics425, 109907 (2021)","venue":null,"work_id":"d0915b91-f6c6-4afe-8041-979968d50946","year":2021},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.231129Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:7ab084ff70ded9c1459bbf9539ee9e7ce77b63273e84d080c02cae3e51e563d4","observation_id":"36b22aae-8229-4f7b-998c-4f2b99c12070","resolution":{"observed_at":"2026-08-12T18:34:44.809739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.798173Z","title":"In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (2019)","venue":null,"work_id":"0fb02a8d-6bd6-48e2-bc1e-baa67e93ad47","year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.234551Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:da3ed519fcaf45cf093920a5ad40769038617b37cc4317374b4e0948495499c7","observation_id":"dcfeb2a3-fa8a-4dda-b8d9-250d4eee419c","resolution":{"observed_at":"2026-08-12T18:34:44.801204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.790420Z","title":"In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (2018)","venue":null,"work_id":"c66ec380-abee-44df-9c44-bfed5b785850","year":2018},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.238657Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:2eaf12c28cf4e0b02fa83b53e30478b1e0f56acc7efef0df4ec7821d21ea1453","observation_id":"659221e0-8ba8-4d01-9405-ef1533673452","resolution":{"observed_at":"2026-08-12T18:34:44.793055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.782211Z","title":"In: Proceedings of the International Conference on Machine Learning (ICML) (2018)","venue":null,"work_id":"bc327d83-23c2-4612-8718-9b13df0531ec","year":2018},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.241646Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:dc13902245ec45957e5fa429b68323f7480f3b4ed39985ff9335be76a1cb6133","observation_id":"07859901-19e3-4288-a6ba-bf01885c3978","resolution":{"observed_at":"2026-08-12T18:34:44.785046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.773572Z","title":"In: Advances in Neural Information Processing Systems (NeurIPS) (2022)","venue":null,"work_id":"41215607-89b1-49d9-8c10-1527a3927d99","year":2022},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.244894Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:2cc232805099ec3c73fb60868761db3ac79a4f4d64642c2ca73c7621d6fc3c07","observation_id":"9a3ee68d-11ef-4f58-addb-1b7b6c24c12d","resolution":{"observed_at":"2026-08-12T18:34:44.776812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.764738Z","title":"In: NeurIPS Workshop on Machine Learning for Physics and the Physical Sciences (ML4PS) (2019)","venue":null,"work_id":"65521ebf-845c-4700-8ea4-96e73d1fbfd8","year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.247654Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:c25d4311ebd18412a3b9f46ae429692cd54942a3db20d927398d577fa3e7c6ab","observation_id":"6df9a457-3266-49a9-82c1-ac258f823677","resolution":{"observed_at":"2026-08-12T18:34:44.768116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.250530Z","title":"In: Advances in Neural Information Processing Systems (NeurIPS) (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.250530Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:0a5ae353a37cddc070c6ac0e7281892a12a1cd3a84eda5384ef2a8624391fe88","observation_id":"0ce5033a-3016-4f24-a7f2-c851cef6e083","resolution":{"observed_at":"2026-08-12T18:34:44.250530Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.253469Z","title":"Journal of Computational Physics378, 686–707 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.253469Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:66675da3bdf2dcecf7d1985b46d84c7c1ac1cbf86167b77bc0a0d427302fedb3","observation_id":"8c2692c0-d962-4812-85a7-c581749b4134","resolution":{"observed_at":"2026-08-12T18:34:44.253469Z","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":"2026-08-12T18:34:44.746097Z","title":"In: International Conference on Learning Represen- tations (ICLR) (2020)","venue":null,"work_id":"b9eec371-c50c-418b-9f8f-f317cd4566eb","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.256192Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:8237d1c49515cbfce705fcc8b9dc9f6610659f82ec51fc7fed0b787046e09e20","observation_id":"91794c5d-135b-4611-acdb-ecf6f91b540e","resolution":{"observed_at":"2026-08-12T18:34:44.749069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.737945Z","title":"In: Advances in Neural Information Processing Systems (NeurIPS) (2018)","venue":null,"work_id":"5f59259f-8bb3-4935-bc1e-fb2ed3262209","year":2018},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.258954Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:8feef1c959e73902fa48f2b7e3ae7f77767429705fa30f2a95e4281c2e80e758","observation_id":"a148fdbc-55dc-401e-bea4-b48de54a744b","resolution":{"observed_at":"2026-08-12T18:34:44.740900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.729376Z","title":"In: IEEE/RSJ International 45 Conference on Intelligent Robots and Systems (IROS) (2018)","venue":null,"work_id":"fd8ed62a-f1c6-4a8b-8a46-5407bc0ee94b","year":2018},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.261712Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:5582a50d603f8b8236b64af890e91a81e4ca4da80e64f901183ae836ba2c5a64","observation_id":"1948397f-90e8-4c3a-97d1-ae8a71a37a53","resolution":{"observed_at":"2026-08-12T18:34:44.732270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.721569Z","title":"In: Advances in Neural Information Processing Systems (NeurIPS) (2021)","venue":null,"work_id":"34a0f31a-daa8-4969-a470-a87deda3d785","year":2021},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.264400Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:b4e097d796d6e1795f2d71fa94bb07ad3139c7b50c4c3a0b3cfbcce05963ac44","observation_id":"ed629fab-9f0a-4718-94e7-215e78d1498b","resolution":{"observed_at":"2026-08-12T18:34:44.724279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.712533Z","title":"Physics of Fluids33, 027104 (2021)","venue":null,"work_id":"2e0490cc-dd1f-4146-8f4e-5ca22cc547c0","year":2021},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.267214Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:914edff81a84d084aa5752894c70cfa549d6c2119ba7dd6aad516a33cf1663cd","observation_id":"a2e0db3c-4e1a-4cee-b09a-dbbb8e0b0d43","resolution":{"observed_at":"2026-08-12T18:34:44.715917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.703474Z","title":"In: International Conference on Learning Representations (ICLR) (2021)","venue":null,"work_id":"01579ecc-f407-4b9a-b4f6-c68cbe09bdf3","year":2021},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.272222Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:45083b29c5bd7f583e350f711de11d8d1ae2a4d59ff816b9719c3832a901b87a","observation_id":"6027ae37-2563-4279-bd56-370ee587bd2f","resolution":{"observed_at":"2026-08-12T18:34:44.707499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.695194Z","title":"IEEE Transactions on Neural Networks 9, 987–1000 (1998)","venue":null,"work_id":"b6d70fea-b1d2-41e7-a758-369284f40987","year":1998},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.275179Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:d38341a01198b1231bcdbe4f26b32d8af518d7cb3305e3a564ee3c5d3bce1ba1","observation_id":"b2633414-81b9-4634-892a-310362edb828","resolution":{"observed_at":"2026-08-12T18:34:44.698418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.685698Z","title":"Journal of Computational Physics394, 56–81 (2019)","venue":null,"work_id":"f1b8a349-931c-4ea0-943c-b98ead75b0d1","year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.277844Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:33b80bb1030d9effa1cb0c1de4e11f13757eb1180f861cc2c8b45ead0dc2470b","observation_id":"38de211f-5929-462a-a2b3-6d956e40df4b","resolution":{"observed_at":"2026-08-12T18:34:44.690311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.674864Z","title":"Journal of Computational Physics 403, 109056 (2020)","venue":null,"work_id":"09b622f0-70b1-485e-bd45-7fb65a54b483","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.281453Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:76122cc4928ed09ca2ff7a4a50a05276cd14e7e97dabebe565fd1d123a571f6c","observation_id":"6ef13648-6634-4e65-b6bd-8d548980a6a3","resolution":{"observed_at":"2026-08-12T18:34:44.677787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.666873Z","title":"Journal of Computational Physics 406, 109209 (2020)","venue":null,"work_id":"10951098-cdb5-4afb-bdf1-99fdc458a68c","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.284159Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:83c4d935feec0e261fdc6e0c321aebaa8a254d6f61b2363717a5ddc1166de3d4","observation_id":"9a767995-af94-4612-b3f4-ab3f8974f471","resolution":{"observed_at":"2026-08-12T18:34:44.669713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.658923Z","title":"Journal of Franklin Institute346, 898–913 (2009)","venue":null,"work_id":"5cc55f60-a11d-4756-96ab-33c7dbf0b114","year":2009},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.286767Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:9833e260ffba2b2ffc5bfa7c5021478189bdb655cf9d9d2e514e447892c13335","observation_id":"4e79a607-b11b-471c-b144-b74d544a651b","resolution":{"observed_at":"2026-08-12T18:34:44.661675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.650412Z","title":"Communications in Computational Physics28, 2139–2157 (2020)","venue":null,"work_id":"1310c4fa-addc-4c0a-8ca8-10e29f1cde01","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.289553Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:d7b8f099e61797b0b2d4f8ef7b81777c79eb75490800803ec40faf61777475f5","observation_id":"81ecf3df-57f5-4086-a8f8-09923e73e481","resolution":{"observed_at":"2026-08-12T18:34:44.653743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.642400Z","title":"SIAM Journal on Scientific Computing42, 3285–3312 (2020)","venue":null,"work_id":"cec63530-7c23-42fd-86d5-ae3a12e4bf65","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.292275Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:386c34c7e39efe2203e74579f6978f3fcf0fc9258bd0a7c2f0e59916e76981f7","observation_id":"9eb7cd0f-2d2d-47fe-9df3-f9ecf490cf39","resolution":{"observed_at":"2026-08-12T18:34:44.645399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.633859Z","title":"In: Workshop on Integration of Deep Neural Models and Differential Equations at ICLR (2020)","venue":null,"work_id":"170930b3-0751-4af2-898e-5320a88da580","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.295515Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:d945fc63259e90997179e189dec458d9de305622ebd3912712eafec294456ce1","observation_id":"bc770613-9bf2-49ab-92ec-3d177c992eab","resolution":{"observed_at":"2026-08-12T18:34:44.637034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.625519Z","title":"Frontiers in Neurorobotics13, 42 (2019)","venue":null,"work_id":"8d8d4210-c6f1-4cf3-b501-b234272993c5","year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.298650Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:fe863ad0a89324e34a8ff7c5d75b51df03c4b158605d6fa38d8731454f8341e8","observation_id":"4e7dacf6-5956-46a8-a673-5e7ebf1db6c4","resolution":{"observed_at":"2026-08-12T18:34:44.628492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.07457","last_updated":"2020-01-21T11:58:41Z","snapshot_observed_at":"2026-08-15T13:21:19.104458Z","submitted_at":"2020-01-21T11:58:41Z","title":"Learning to Control PDEs with Differentiable Physics","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.07457","snapshot_observed_at":"2026-08-12T18:34:44.301422Z","title":"arXiv preprint arXiv:2001.07457 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.301422Z"},"links":{"cited_paper":"/paper/2001.07457","citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:ce681c850f3dab2400eea02600302a7b82e9b9e0d617557a841ea9e5b63c79e5","observation_id":"2df93976-c7da-4902-a0e1-fd8693538541","resolution":{"observed_at":"2026-08-12T18:34:44.301422Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.304404Z","title":"In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.304404Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:0ffb25a6bc2bdaf9ec5bc6592d61cbd0612061a296eebb7289e2b099ac9655c7","observation_id":"bddbcf94-2259-45b5-8904-2b9278cbd8d4","resolution":{"observed_at":"2026-08-12T18:34:44.304404Z","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":"2026-08-12T18:34:44.616608Z","title":"Available online (2005)","venue":null,"work_id":"208c4d66-d3b7-4b84-a68e-ad1f57dff90a","year":2005},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.307156Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:229fd6458a8447034e0e8ee40f6c47e476264ec8ffebb26e7fac64733ad4bccc","observation_id":"5c2191b5-953b-42d4-a2d4-c6d8fc5e037b","resolution":{"observed_at":"2026-08-12T18:34:44.619950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.607925Z","title":"Agricultural and Forest Meteorology 314, 108777 (2022)","venue":null,"work_id":"81df1cd8-48b7-41de-9890-153f82c6b72e","year":2022},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.311245Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:ca68e5fbdfac39d7c6ae7c1b872268ce6b7a5b0ab39716368d48e79c6b6fb00a","observation_id":"5b30432f-de15-442f-bc80-b4704312b002","resolution":{"observed_at":"2026-08-12T18:34:44.610798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.599619Z","title":"Global Change Biology11, 1424–1439 (2005)","venue":null,"work_id":"8add7bcd-9820-41a6-9145-19c8901e7b74","year":2005},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.314065Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:06328a7fb05071343b6a1d475294b7875bf9d281c15c4c7a06add731ec49b656","observation_id":"06ceea30-63f2-4c61-b89c-de270cd905cb","resolution":{"observed_at":"2026-08-12T18:34:44.602558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.591121Z","title":"Agricultural and Forest Meteorology147, 209–232 (2007)","venue":null,"work_id":"6589058a-a8ac-45dd-8ccb-bfb76b50987f","year":2007},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.316833Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:999b2bccd504aa0858f4b44b01599ae84eada10cf7ccf826425be8113de7f03a","observation_id":"ecde127c-a75c-430b-843d-c39edb4918a8","resolution":{"observed_at":"2026-08-12T18:34:44.594047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.581458Z","title":"Global Change Biology16(1), 187–208 (2010)","venue":null,"work_id":"c8f4f34f-4b1f-4536-847b-0303a987e649","year":2010},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.319474Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:12a93b5590b220b4d1068b99d43abf9aafe96d33868d44baee9f9beca05d7854","observation_id":"37b8d872-be03-4b5e-9438-62718139e066","resolution":{"observed_at":"2026-08-12T18:34:44.585443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.572694Z","title":"Functional Ecology8(3), 315–323 (1994)","venue":null,"work_id":"2aa1649c-1a3b-4064-aa27-5dc83821f2c2","year":1994},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.325647Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:a1b58b6a72bdc45487e0c4c8fb5762c6d75dca34343eeb4ba5ff6082edcad370","observation_id":"7fc8da0b-5411-487e-9cd4-b2f4666c8a9a","resolution":{"observed_at":"2026-08-12T18:34:44.575757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.amc.2007.07.004","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-21T11:03:19.436173Z","title":"Applied Mathematics and Computation196(2), 686–704 (2008) https://doi.org/10.1016/j.amc.2007.07.004","venue":"Applied Mathematics and Computation","work_id":"8f20f5f6-c51d-4f8f-8a31-8db924398fd2","year":2008},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.329045Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:4019cdbc8135cb2ea0da0b5a70677dde1f7ade6ec641bbd64242ce09b9ea0338","observation_id":"7a6ef3fc-5a87-4402-aa2b-76d2e5bd1638","resolution":{"observed_at":"2026-08-12T18:34:44.402606Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.563143Z","title":"IEEE Access7, 127356–127367 (2019)","venue":null,"work_id":"e99adcac-76cf-400d-95f8-67202c0cc5e8","year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.331887Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:c0c1224fa4ef9685c27d667ce932be47b58ce7b9ea1054f96496618838d79368","observation_id":"9c62fd80-6f7c-4f61-8c1f-57fd6f0fc541","resolution":{"observed_at":"2026-08-12T18:34:44.566121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.554167Z","title":"Renewable and Sustainable Energy Reviews135, 110275 (2020)","venue":null,"work_id":"36da53d2-2f1e-4aca-bdea-01b7aff22ab1","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.336154Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:485277180f48551b83ba9cbd1293bb07ebad46d4b11d1303e5710b6ffaac0c0c","observation_id":"5d888b8c-3311-477e-9f44-898d6f99c581","resolution":{"observed_at":"2026-08-12T18:34:44.557435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5285/13896773-01e5-48e6-bfab-c319de46b221","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.389557Z","title":"NERC Environmental Information Data Centre (2020)","venue":null,"work_id":"94a03beb-61b3-4e1d-9f63-3523521a5019","year":2020},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.339158Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:6d85b6f415871d142eded73123e2426a9099dc5f530db1429594eb8a5b2d646a","observation_id":"0784e11a-6626-41f0-aac9-df4316ef44c3","resolution":{"observed_at":"2026-08-12T18:34:44.393408Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41559-019-0809-2","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.380207Z","title":"Nature Ecology & Evolution3, 407–415 (2019) https://doi.org/10.1038/s41559-019-0809-2","venue":null,"work_id":"bd8f401e-1077-4aa1-98c4-69dd017fa91d","year":2019},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.341730Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:df08b5f3723d52ea8bccb33355c5169813b3dc4bb0b53c3bade440061fc91fc4","observation_id":"ed9f5cb2-3a11-4a9e-a1f2-d42249b1cda7","resolution":{"observed_at":"2026-08-12T18:34:44.383606Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5194/bg-15-5015-2018","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T18:34:44.369171Z","title":"Biogeosciences15(16), 5015–5030 (2018) https://doi.org/10.5194/bg-15-5015-2018","venue":null,"work_id":"e2911a35-c60e-4c63-9bc8-5cb7c52ccfc6","year":2018},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.344316Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:aea8f8e3a4e617b93a179862f112addfedccbd5be82b647d685c6660271170f3","observation_id":"3c137c11-a3ae-4569-85aa-a1982e88cad7","resolution":{"observed_at":"2026-08-12T18:34:44.374643Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-12T18:34:44.348654Z","title":"IEEE Transactions on Computational Intelligence and AI in Games9(1), 54–66 (2017) https://doi.org/ 10.1109/TCIAIG.2016.2565661 48","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T18:34:44.348654Z"},"links":{"citing_paper":"/paper/2411.11497"},"observation_digest":"sha256:d4b941e340012835ee765317f2942d0486d025f4932a90912b59893000de8745","observation_id":"56830995-1c77-4e02-ace4-303f5c8d98f0","resolution":{"observed_at":"2026-08-12T18:34:44.348654Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.11497","last_updated":"2025-07-07T16:30:17Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T16:59:56.544745Z","submitted_at":"2024-11-18T11:58:20Z","title":"Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":6,"verified_exact":5,"verified_fuzzy":30},"total_outbound_references":43},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2411.11497."}