{"as_of":"2026-08-08T09:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:270cb001645f2b0d689a5455cf2253c4d1737c7421faee29157fc11999322a6b","coverage":[{"denominator":54,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:03:16.209528Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:24:40.657236Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T17:24:46.971086Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"cited_work":{"arxiv_id":"2507.04027","doi":null,"metadata_source":"pith","pith_arxiv_id":"2507.04027","snapshot_observed_at":"2026-08-06T17:24:46.971086Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","venue":"cs.LG","work_id":"f211c962-736a-43a4-a73d-69997fbb784c","year":2025},"citing_paper":{"arxiv_id":"2507.11057","last_updated":"2025-07-15T07:47:03Z","snapshot_observed_at":"2026-08-06T17:15:49.664279Z","submitted_at":"2025-07-15T07:47:03Z","title":"Urban delineation through the lens of commute networks: Leveraging graph embeddings to distinguish socioeconomic groups in cities","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T17:24:40.657236Z"},"links":{"cited_paper":"/paper/2507.04027","citing_paper":"/paper/2507.11057"},"observation_digest":"sha256:fc2a482582f3fdb09293c5a75a9175132dd8490d45bbfcfc4d96a94126e6bf37","observation_id":"22418715-20e8-46bc-b7c4-380779149e63","resolution":{"observed_at":"2026-08-06T17:24:47.172121Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.04027/citation-record","integrity":"/paper/2507.04027/integrity","json":"/paper/2507.04027/citation-record.json","paper":"/paper/2507.04027"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:03:18.683908Z","title":"Rosvall, A","venue":null,"work_id":"118ba5bd-e168-40e1-9120-ff946c24dcdf","year":2005},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.076404Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:345a1525d82c09349e86a93386cdb745ab291357abb3479cf7fc3a0c4e9a50dc","observation_id":"aa0918ed-3e25-4cd4-b83e-ba3198cfc255","resolution":{"observed_at":"2026-08-06T20:03:18.688980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.668252Z","title":"Pflieger and C","venue":null,"work_id":"ce5fab01-fe6f-4177-a0e3-c1f2b502f1bd","year":2010},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.121791Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:99a606b351ab8a48ac3f6162d707aec76f1fbbcc0fd0ceb75099c40616996415","observation_id":"9ea82d32-5c52-459e-862b-388ac93ca869","resolution":{"observed_at":"2026-08-06T20:03:18.672533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.652840Z","title":"Jiang and C","venue":null,"work_id":"ef6f8e54-e338-47fd-90fc-e4e6e5367f0b","year":2004},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.151368Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:51df31d38d8949a27a19e9596d16927c903108f19cda80f0ae7d0b19ad24b336","observation_id":"5ab7a421-e012-409a-a0d0-a42f9d57ed34","resolution":{"observed_at":"2026-08-06T20:03:18.657133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.636900Z","title":null,"venue":null,"work_id":"6f33bd7a-4e7f-4bf3-a5af-8ff95a73b990","year":2017},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.209270Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:9441181ca0e267302e03391ee8389123c322b87afdd372bf7607570001c141b6","observation_id":"11cde00f-6ae6-427c-b53f-8d20ed42fd3e","resolution":{"observed_at":"2026-08-06T20:03:18.641889Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.621155Z","title":"Urban road network expansion and its driving variables: A case study of nanjing city","venue":null,"work_id":"6fd0ebc7-ff98-436e-845e-bf3083d3efc6","year":2019},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.253579Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:a44d2f76507f505de30293541ab5322f5fadfc208b7524a0b128155e0cf220fc","observation_id":"a160aa57-92d0-4c45-9f51-6a310504f170","resolution":{"observed_at":"2026-08-06T20:03:18.626032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.604023Z","title":null,"venue":null,"work_id":"27a87352-b223-4c32-b2f2-8a8c9dd792bf","year":2018},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.307026Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:5ae427323bec1d1dc2e847514ab5f45991f2bca775dd351e595277e37ce41b07","observation_id":"29ab50fa-bc4c-4939-8f5b-d105f03689d5","resolution":{"observed_at":"2026-08-06T20:03:18.609451Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.588110Z","title":"Lee and J","venue":null,"work_id":"c9233f1a-236d-4671-82fa-05e776f86a49","year":2018},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.363479Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:a965eb365ae264ae078dc460ab4d4f137481a0669eede64c518707331544550e","observation_id":"5abac61f-8d81-4d32-8ca2-ad7b0c17667d","resolution":{"observed_at":"2026-08-06T20:03:18.592680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.571998Z","title":null,"venue":null,"work_id":"264f496c-8060-4ef6-b53a-e56e7ed96e4b","year":2017},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.407883Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:faede1b3ea54f6091c1bdf04677e34ce1f1f995e0ae86a32c06e6bcafb21c4a1","observation_id":"251a3428-70d7-4eab-8e4b-a46cde7f2ba9","resolution":{"observed_at":"2026-08-06T20:03:18.576597Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.555676Z","title":"node2vec: Scalable feature learning for networks","venue":null,"work_id":"a702264d-0816-4831-955c-4bcfbc2ade2b","year":2016},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.467403Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:eb87bf7c2ed64415bb0cd55593f1a08a1e9d22489c6fcfefef62075bb92ba6cf","observation_id":"1802462b-6770-4647-985d-142a6615466f","resolution":{"observed_at":"2026-08-06T20:03:18.560698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.540214Z","title":"Line: Large-scale information network embedding","venue":null,"work_id":"ac02a854-7faf-4bda-8685-d3786e923458","year":2015},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.520174Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:97351309ff34451886ce900f437f11696425d4951c8cce8eafbddc36fd657318","observation_id":"58ae9cfc-fb10-4721-adb1-23bcf54107d2","resolution":{"observed_at":"2026-08-06T20:03:18.544883Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-06T20:03:12.542326Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.542326Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:4dbf8771f0290a257295b008888e787208469ae4b1a3a1ae0c8bffbbc57cf76d","observation_id":"686e489a-8a40-4a92-971d-c3e69e0b60e2","resolution":{"observed_at":"2026-08-06T20:03:12.542326Z","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":"2026-08-06T20:03:18.524013Z","title":"Sobolevsky and A","venue":null,"work_id":"28e7fa49-95a2-47d3-95a9-399cef732602","year":2022},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.608117Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:b6d77a8af749b5d0a74f16ec8de5e4b267364a165df0b394738bc9b49cc98c02","observation_id":"dc98524e-d566-49cd-be94-3422070c6bc1","resolution":{"observed_at":"2026-08-06T20:03:18.528483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.508373Z","title":"Velickovic, G","venue":null,"work_id":"67b6c8b9-669a-482b-9a65-3c52a828b50b","year":2017},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.664059Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:697897e14cdf7d9e9e7b4943d4e30fc4265ffcd0eabf253cf36fd31a6eb90d85","observation_id":"000867b6-bb31-4fd7-8d03-fda764cd2daf","resolution":{"observed_at":"2026-08-06T20:03:18.513129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.492050Z","title":"Kempinska and R","venue":null,"work_id":"67d5c20b-e3f5-4918-8139-a9f40e59a4e6","year":2019},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.706296Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:d11c383f7760b216bbca3610471620961a6e46b67c40227a5276c6c5a0a5fe54","observation_id":"0b784a32-e314-4bb0-ac2a-fc7a0104abee","resolution":{"observed_at":"2026-08-06T20:03:18.497118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.475244Z","title":"Pagani, A","venue":null,"work_id":"ae5ecf68-26cc-4ec2-98e4-4eecdd61d633","year":2021},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.818343Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:26292f66f9ff82b36fd329b6ae86f43ef48d74a04214d184c87744c30c2b0ea1","observation_id":"fd594afe-fde5-4095-981a-00c77dc501c4","resolution":{"observed_at":"2026-08-06T20:03:18.480878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.455833Z","title":"Huang, D","venue":null,"work_id":"ef494694-a1f9-4ef1-b9c3-d90796148b9e","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.878880Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:333fd17556a380796c1c2323bb8a895c2a33ec701dcc823d7a2ba8ef0cb1250d","observation_id":"672e4ae0-3b08-4624-825a-a50b19b8e5ae","resolution":{"observed_at":"2026-08-06T20:03:18.461604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.09021","last_updated":"2022-02-18T04:59:20Z","snapshot_observed_at":"2026-07-06T12:39:02.767876Z","submitted_at":"2022-02-18T04:59:20Z","title":"Effective Urban Region Representation Learning Using Heterogeneous Urban Graph Attention Network (HUGAT)","version":1},"cited_work":{"arxiv_id":"2202.09021","doi":null,"metadata_source":"pith","pith_arxiv_id":"2202.09021","snapshot_observed_at":"2026-08-06T20:03:16.415490Z","title":"Effective Urban Region Representation Learning Using Heterogeneous Urban Graph Attention Network (HUGAT)","venue":"cs.LG","work_id":"d03a9d47-1086-4a01-a9ed-7901b3128053","year":2022},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:12.907871Z"},"links":{"cited_paper":"/paper/2202.09021","citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:916587ba38951e3d3e744d8a730f93e9da8a642f9d8fefaec715f1abc9887fb8","observation_id":"59be4ee9-175b-45be-b6fc-c9b4ab2940a4","resolution":{"observed_at":"2026-08-06T20:03:16.482081Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.439423Z","title":"Mishina et al","venue":null,"work_id":"21fe91e1-15d6-481a-9dab-9694ff5d28af","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.020927Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:a087dea9869e5343f91d99096019a595bf3cbbfde89272493ac7ba7a745490a4","observation_id":"e3983c36-eaf9-425e-b439-737ac6737727","resolution":{"observed_at":"2026-08-06T20:03:18.444514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.423693Z","title":null,"venue":null,"work_id":"02bec29b-7034-4838-9272-e94005dce22f","year":2019},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.139491Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:3f93be60d827a643ee81f77adc745c6100634d87c11b2eae5bdbef94c9cde162","observation_id":"39189e9a-f30f-4d09-8ba3-2d001fbf697b","resolution":{"observed_at":"2026-08-06T20:03:18.428351Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.407149Z","title":null,"venue":null,"work_id":"3d68530e-85d9-433e-907a-163426ae3fe8","year":2009},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.286000Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:7d2328366da6d06e908c689c3f9e770e3c46db8be69d6c8aeb7f39102af80e28","observation_id":"1597fbb0-436b-43bf-a2a7-7385d9bb1707","resolution":{"observed_at":"2026-08-06T20:03:18.412242Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.387816Z","title":"Graph neural network approach to predict the effects of road capacity reduction policies: A case study for paris, france, 2024","venue":null,"work_id":"610535f0-8a0c-4c08-8382-34f2ce7e01f0","year":2024},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.333348Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:7c476f3050e1ba503c9ac3239aeebd65a9c48e7422c1f070754de985693b3531","observation_id":"62e09b3a-ba67-4667-bae3-67a1f6f426f0","resolution":{"observed_at":"2026-08-06T20:03:18.393793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.368605Z","title":"A multi-modal graph neural network approach to traffic risk forecasting in smart urban sensing","venue":null,"work_id":"f2213ccb-8a8f-42e4-88df-38aebf4e8b79","year":2020},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.484404Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:0cccb8f023de5ff108be06fdc61c58a199074cf4395527880e85a577a55b1d80","observation_id":"477fecec-74d2-48d9-bf21-00bcd41b5983","resolution":{"observed_at":"2026-08-06T20:03:18.373818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.350497Z","title":"Heterogeneous graph neural networks with post-hoc explanations for multi-modal and explainable land use in- ference, 2024","venue":null,"work_id":"8eaab763-47f9-4cd4-ab9b-aa5f3df6be31","year":2024},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.522193Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:11205242005908b56b2628003b579499826b36f7f23b3f0962b5ea947d5cfa92","observation_id":"a26d8f3b-495a-4535-914e-e64d8fd0a4ce","resolution":{"observed_at":"2026-08-06T20:03:18.355642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.332469Z","title":"Khulbe, A","venue":null,"work_id":"bfdef660-e296-4e56-b158-f46e7b9a36f6","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.625466Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:39e65bde1ccb0592093969baf3e699dacecd34d03fe66c621be669b299fbaf0a","observation_id":"a5d16ebb-6af7-40fa-afcb-674b1c715485","resolution":{"observed_at":"2026-08-06T20:03:18.337927Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.316357Z","title":"Longitudinal employer-household dynamics","venue":null,"work_id":"8c88d8a1-01e7-4e3e-b957-8949950cda99","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.718979Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:192efbf3602fb5d01f4f3848a66ad04f938b37aabbc51f3a63a1e97d9121f7d9","observation_id":"367005ec-6d01-4605-ac90-36a4f736a047","resolution":{"observed_at":"2026-08-06T20:03:18.321044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.299129Z","title":"American community survey data","venue":null,"work_id":"79d220de-d5ef-4c04-8523-c5ff8985bc35","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.858250Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:a8aa173d327fb17c56f7ef2984e6e3bbba0c0ef63584675f85dabe431d543a35","observation_id":"a8f78e51-086e-49fb-8e0f-290fdf45826c","resolution":{"observed_at":"2026-08-06T20:03:18.305154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.281753Z","title":"Nyc 311 data","venue":null,"work_id":"9f7dea7e-b72d-450a-ac4b-5cd6d6fe9e68","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.913900Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:25df94158c9cef709529888dee7f79c1bfbdace4f37164ed2e2c28e3c32e5f2d","observation_id":"2ae7df9b-b626-489f-ae71-57fd3387736e","resolution":{"observed_at":"2026-08-06T20:03:18.286826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.264150Z","title":"Direction aware positional and structural encoding for directed graph neural networks","venue":null,"work_id":"bf46d8b8-1a66-491b-b14c-c5cc039b5cdd","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:13.965813Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:e6a3f759b2e759947b5e209915f1e988757a5603db5ec24488a6dfac3961108d","observation_id":"d224dc2e-47fb-452f-9f7c-bc05ceb1ab35","resolution":{"observed_at":"2026-08-06T20:03:18.269556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.09699","last_updated":"2021-01-24T09:38:54Z","snapshot_observed_at":"2026-08-05T19:35:00.334774Z","submitted_at":"2020-12-17T16:11:47Z","title":"A Generalization of Transformer Networks to Graphs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.09699","snapshot_observed_at":"2026-08-06T20:03:14.054083Z","title":"Dwivedi and X","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.054083Z"},"links":{"cited_paper":"/paper/2012.09699","citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:1fd9385b7b015d4f37dd86af5c6c4fa79f40c784fd7372a6d15363714472ec08","observation_id":"3bc3d7de-fb36-411f-9404-c347d1e73473","resolution":{"observed_at":"2026-08-06T20:03:14.054083Z","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":"2026-08-06T20:03:18.245480Z","title":"Recipe for a general, powerful, scalable graph transformer.Advances in Neural Information Processing Systems, 35:14501–14515, 2022","venue":null,"work_id":"2d7a98ec-c406-40e1-9613-912f607d84fa","year":2022},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.167130Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:bd486ace184e223f48d350403944933cefc1b61d8d8c1a4674eafe45678a3b86","observation_id":"0c4f99f6-050c-4b74-8121-30ff3597cec3","resolution":{"observed_at":"2026-08-06T20:03:18.250973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.228004Z","title":"Rethinking graph transformers with spectral attention","venue":null,"work_id":"033bbfef-3eed-4a60-be2a-d3cebe086336","year":2021},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.294297Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:9565d106350db7f38fd8fecdedbc61718094c53b9fd57888b283e402a2c38d9e","observation_id":"8a599643-b295-45c2-8b76-541d42c33396","resolution":{"observed_at":"2026-08-06T20:03:18.234107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.213192Z","title":"Do transformers really perform badly for graph representation? In Advances in Neural Information Processing Systems, 2021","venue":null,"work_id":"ed8ed947-848d-4ca9-a7f9-1bfc52fa339d","year":2021},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.418349Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:d0b117dbba62c6b99659da0096b10e2de689d2bfcb5b42cd9980b5e323cded10","observation_id":"d516ad65-d586-4a29-8203-32af2ba5e65a","resolution":{"observed_at":"2026-08-06T20:03:18.217751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.197305Z","title":"Distance encoding: Design provably more powerful neural networks for graph representation learning","venue":null,"work_id":"b063369c-1482-4f92-b6bd-06151fbd0079","year":2020},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.508745Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:73d4564d6b97b7f7e91d2ece81a2e3d9e622909d66f9573822537b6ad40a2479","observation_id":"f0fc1cf5-ae68-4639-abfc-5caf7d3d10f7","resolution":{"observed_at":"2026-08-06T20:03:18.202510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.181594Z","title":"Graph neu- ral networks with learnable structural and positional representations","venue":null,"work_id":"5e6955a7-7829-44da-bb28-c7a151dac6a3","year":2022},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.626539Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:469482394c0ba7704e656971074305fb283a1890d459c5f5f2eaecbce9ec2f6d","observation_id":"77f6e65a-351c-473f-bbf2-1dce815efcb2","resolution":{"observed_at":"2026-08-06T20:03:18.186330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.12674","last_updated":"2023-12-13T13:18:05Z","snapshot_observed_at":"2026-07-06T12:32:33.844861Z","submitted_at":"2022-01-29T22:26:02Z","title":"Rewiring with Positional Encodings for Graph Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.12674","snapshot_observed_at":"2026-08-06T20:03:14.751068Z","title":"Rewiring with positional encodings for graph neural networks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.751068Z"},"links":{"cited_paper":"/paper/2201.12674","citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:2f90de0ff381f105d78402b3c0291efc85d946ee2ef12c976b39415fbcba8955","observation_id":"30462b16-fe07-47c4-b78a-dd24fde8063c","resolution":{"observed_at":"2026-08-06T20:03:14.751068Z","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":"2026-08-06T20:03:18.165908Z","title":"Sume: Semantic-enhanced urban mobility network embedding for user demographic inference","venue":null,"work_id":"fb190c9b-5807-4e4a-8f9d-811b0d64c041","year":2020},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.864762Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:139e6a7afae645942845e0c9f0bcba219f742ef7369e37f4cf6809181bdbbf0e","observation_id":"9afc02b0-10fc-416c-94c0-1e030ab50fae","resolution":{"observed_at":"2026-08-06T20:03:18.171016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.150322Z","title":null,"venue":null,"work_id":"f0817367-d2fd-42be-8228-e5d07aeeaa09","year":2021},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:14.963893Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:5380a89fdae235d2522256a96fac583dc242cbf44261f460f271da1bb332326c","observation_id":"28c3dfef-58b9-4b91-8dbb-0929d68789f8","resolution":{"observed_at":"2026-08-06T20:03:18.154680Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.134887Z","title":"Jain and Richard C","venue":null,"work_id":"3c846273-4377-4bae-9613-4b37ea9d082f","year":1988},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.029819Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:de5329cd40de19ec21d1c108f142be2d02c49a1db49b8bc762c8924a46463125","observation_id":"bb9f6088-0b8e-42ab-96c9-ad5ac639cd2e","resolution":{"observed_at":"2026-08-06T20:03:18.139184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.119748Z","title":null,"venue":null,"work_id":"af04454b-c80b-4aad-9161-14478e37f514","year":2024},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.097371Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:9521cb0c51e10343a52ace15feb99c97c6baf94c7690d1edb2642ca0d0799530","observation_id":"085f9f0a-361c-451c-aa0a-043075f0ecff","resolution":{"observed_at":"2026-08-06T20:03:18.124394Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.103736Z","title":"Distance deterrence comparison in urban commute among different socioeconomic groups: A normalized linear piece-wise gravity model","venue":null,"work_id":"8e51e9b4-0213-478b-bed3-07b292ca768d","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.178120Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:e71fd8bdf8003035499b202aae6259dc3274b2fa8be435714373c4cfd200128a","observation_id":"f4d2d34a-76ad-440a-9d1e-ec293b444c98","resolution":{"observed_at":"2026-08-06T20:03:18.108961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.087721Z","title":"Impact of income on urban commute across major cities in us","venue":null,"work_id":"3419af0e-cf3b-40b9-a851-75968a1f9b3f","year":2021},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.246709Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:ce56ab88f9329221a849b94d9f356c1e4eb5bebf535ede9334cdeaabc8ca0298","observation_id":"46d445f3-da2c-41f1-9fe1-0508e3c5a0dc","resolution":{"observed_at":"2026-08-06T20:03:18.092878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.00826","last_updated":"2019-02-22T19:15:54Z","snapshot_observed_at":"2026-07-06T07:05:24.565760Z","submitted_at":"2018-10-01T17:11:31Z","title":"How Powerful are Graph Neural Networks?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.00826","snapshot_observed_at":"2026-08-06T20:03:15.319721Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.319721Z"},"links":{"cited_paper":"/paper/1810.00826","citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:3a86113fc5441d0d9c079391a6f2802baf1d96bbb3341149cfb7985c229d5256","observation_id":"0f728a98-1997-4917-9612-a148f5ffdca4","resolution":{"observed_at":"2026-08-06T20:03:15.319721Z","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":"2026-08-06T20:03:18.072512Z","title":"Hicks and P","venue":null,"work_id":"75b35e3a-fcb8-48e7-9be3-0658149bf1bd","year":1979},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.409264Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:45ea2f13589d136274d8473d49621161b48461d8f494ed3305b5ddf338fe957f","observation_id":"1ef6c569-740c-4b20-b7b5-64a40731854b","resolution":{"observed_at":"2026-08-06T20:03:18.077160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.056146Z","title":null,"venue":null,"work_id":"11fa819e-5b94-4faa-a3e0-dedf5403158a","year":2000},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.512958Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:7cb4c2487ae37f43e8747643123eccc48aced29c0141e62e24c2db4c0be754aa","observation_id":"e17a8b47-51af-47e8-9aa6-a887a0ba546e","resolution":{"observed_at":"2026-08-06T20:03:18.061229Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.040170Z","title":"Leslie and Breandán Ó hUallacháin","venue":null,"work_id":"cc1fbc0a-1b25-4bcb-9f06-730b36dd6ef4","year":2006},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.597844Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:31ee64a1280846b358f2ccdef069138cc991de917c6ab83d6a9458220680979a","observation_id":"56b003cd-bb99-409b-9402-0c8add126553","resolution":{"observed_at":"2026-08-06T20:03:18.044936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:18.024216Z","title":"Structural deep network embedding","venue":null,"work_id":"2bfc2f89-0840-4038-b4b5-97efb5ddba54","year":2016},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.643673Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:56e216e3951d5c47d7b8498cadbecc714426b91384f87ec601af673909ce7d42","observation_id":"145e1582-1e00-4415-ab68-564a71ff2246","resolution":{"observed_at":"2026-08-06T20:03:18.028956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:17.854438Z","title":"Aggarwal, and Thomas S","venue":null,"work_id":"7e04c1be-4939-4a6e-bfcc-e6494ff79def","year":2015},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.709587Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:ca5eab3ebea33be9a191bf4c74241785dba19ea0d62b66555355bad5d61a5df5","observation_id":"e9b8932e-c237-4170-8de8-efe0a029d8e9","resolution":{"observed_at":"2026-08-06T20:03:17.979622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:17.616260Z","title":null,"venue":null,"work_id":"27fcd5d3-bf81-4bc2-8d37-7c54d54cd271","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.769252Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:d6bc0aee4b4c6a9c614523beba56a3457ce7c1ba5a0ca5ba8ee4b41a5c384a61","observation_id":"b86d683b-9f98-4571-8702-0bc45743cec5","resolution":{"observed_at":"2026-08-06T20:03:17.751768Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:17.375280Z","title":"Yap and F","venue":null,"work_id":"c5cdb7ea-752c-45a6-ac40-75b3fc167c78","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.841203Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:b9d1ef2e0f7f8fe876d0a3c4ee33c67d8143579a6247d49fa11b33f8dbae11a7","observation_id":"ff6bfc79-cf90-4b7e-88f8-1864c1520cb1","resolution":{"observed_at":"2026-08-06T20:03:17.467357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:17.170737Z","title":"https://data.boston.gov/dataset/311-service-requests/resource/ f53ebccd-bc61-49f9-83db-625f209c95f5 , 2023","venue":null,"work_id":"602e5d12-447b-4917-a8c9-ebee377027f2","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:15.942431Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:220691328c6ffc9ca1ead82f10f2f8472162b05a99a0c59bfb7bf71729838e80","observation_id":"e6d2ad28-0cae-4171-ba65-3e26e821fb59","resolution":{"observed_at":"2026-08-06T20:03:17.250048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:17.073738Z","title":"https://data.cityofchicago.org/Service-Requests/311-Service-Requests/ v6vf-nfxy, 2023","venue":null,"work_id":"4da1e8ec-ba84-49ce-bf7e-13027426cff9","year":2023},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:16.004133Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:a55fea3c9e1d139c6ef25b62e222a344efa4fcb5114ebe1774ca189e4e73e885","observation_id":"bc0582eb-8697-423d-af8f-6abb45dec698","resolution":{"observed_at":"2026-08-06T20:03:17.116619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:16.889384Z","title":"The pagerank citation ranking: bringing order to the web","venue":null,"work_id":"c7cb1c34-284b-4012-9ac6-931be556b482","year":1998},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:16.087193Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:7c47400e4163d24e12cd03e8e49fc1ba00cd59facd3f0fc19130638788d0e016","observation_id":"3a630537-82ed-4c71-a68a-a9cacafb4f95","resolution":{"observed_at":"2026-08-06T20:03:16.969368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:16.746000Z","title":"Measuring the vibrancy of urban neighborhoods using mobile phone data with an improved pagerank algorithm","venue":null,"work_id":"5f5d6afe-42c5-493e-b58d-094dd61abe06","year":2019},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:16.154910Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:9b4e64428c0c3b37a640b763b8e91749cbb7a1e00ec1c70fb7abd0ad200bed5a","observation_id":"31c9bc7f-fff6-4c29-ba7f-563393c2f6bb","resolution":{"observed_at":"2026-08-06T20:03:16.801564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:03:16.609568Z","title":"Ranking spaces for predicting human movement in an urban environment","venue":null,"work_id":"ffd0b37b-0013-4705-986f-eb45758f1683","year":2009},"citing_paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T20:03:16.209528Z"},"links":{"citing_paper":"/paper/2507.04027"},"observation_digest":"sha256:4e2268d47c4a1839f39c8f036c28f93c434e8e7bd0f6890ee42e1731b19a210c","observation_id":"09328b98-2330-4fc5-a951-b412e745f10d","resolution":{"observed_at":"2026-08-06T20:03:16.655699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.04027","last_updated":"2025-07-05T12:38:59Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T19:54:51.219987Z","submitted_at":"2025-07-05T12:38:59Z","title":"Commute Networks as a Signature of Urban Socioeconomic Performance: Evaluating Mobility Structures with Deep Learning Models"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":13,"verified_exact":1,"verified_fuzzy":40},"total_outbound_references":54},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2507.04027."}