{"as_of":"2026-08-07T06:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3953fd18498bf016d79a08a40da4bdb2f76657b5eb56f715416ccfc45045cbe3","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T13:17:11.093376Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2507.20838/citation-record","integrity":"/paper/2507.20838/integrity","json":"/paper/2507.20838/citation-record.json","paper":"/paper/2507.20838"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:17:11.792244Z","title":null,"venue":null,"work_id":"318fff7d-c8c5-46ec-8cf8-a2b7bd6169a2","year":2024},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.901210Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:816aa061ff1ea703a5c8d019827f096557d7943e3ae1c103e134fccbf9265374","observation_id":"7bcb8516-423b-4e2c-bf5f-401d4d6e6938","resolution":{"observed_at":"2026-08-06T13:17:11.796085Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.779213Z","title":null,"venue":null,"work_id":"1a0f0ace-10f2-439a-a450-02319d8c8f63","year":2019},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.905975Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:24cf8b581e79581dcc7b80446e24344511530321a6d4aeccd40b69c2ffc867eb","observation_id":"04df34ca-14df-4c65-9a99-3a892c368779","resolution":{"observed_at":"2026-08-06T13:17:11.782977Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.766283Z","title":"Ilbeigi, M","venue":null,"work_id":"fcaad1aa-9296-4db2-bf55-b57aa908e618","year":2020},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.910753Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:66e8f3d67bacbe09aa9a1b324a01e88005310b8ff18430172c56e7163e81eed4","observation_id":"b799c28c-467e-4333-a386-dd039449487f","resolution":{"observed_at":"2026-08-06T13:17:11.770004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.753175Z","title":"Zhang, J","venue":null,"work_id":"8a149ca0-01fb-46c3-bc7d-3d9960cce5fd","year":2020},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.915042Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:58acb68a9cc0c3d9b071d423e79e51459d21edd88e961f6ddeb48dc7c70dd076","observation_id":"b70b4176-054c-4f7f-944d-817da1fc3572","resolution":{"observed_at":"2026-08-06T13:17:11.757179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.740035Z","title":null,"venue":null,"work_id":"68fe7796-7fd7-4c62-b180-66a92a7c3780","year":2020},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.919096Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:bbfa29904236de2d2f50c80baedbe0961b4f6d680ba21d2cb24b7290504ab8a0","observation_id":"bdceb9cd-3c94-4ff9-b555-b04ff1b8c351","resolution":{"observed_at":"2026-08-06T13:17:11.743870Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.726443Z","title":null,"venue":null,"work_id":"2c60fe0c-d1ee-4920-847f-0d758dc49e42","year":2024},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.923213Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:3fdb54b2d706f70e849830f7d9795143bc46d2c2372e58a7e5fe64c2a7c16939","observation_id":"988c6974-bf41-41d5-aea5-ce4a88e2e92a","resolution":{"observed_at":"2026-08-06T13:17:11.730507Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.712699Z","title":null,"venue":null,"work_id":"378f7722-012b-407a-b604-575d2c22cd1e","year":2024},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.928162Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:83564ba63637520af851d047dd14a63a80ca5b9f7a57dd0bd5c2a8422594f498","observation_id":"6e73b203-a5ac-4fef-8e5d-b190b383dc09","resolution":{"observed_at":"2026-08-06T13:17:11.717134Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.699136Z","title":null,"venue":null,"work_id":"6d3e1ad4-3d00-44d6-8a77-e4947713290e","year":2017},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.932169Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:7661b426da952ef544ae1dbc9a10c8177985ee4e9e6f605d8adc93476a14d971","observation_id":"9a519d38-f8a7-441f-a869-87bb0ddefce6","resolution":{"observed_at":"2026-08-06T13:17:11.703218Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.685569Z","title":null,"venue":null,"work_id":"9da5abb1-5d02-4be6-a254-a188cb0c0b7a","year":2021},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.936193Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:8804ef5a166e810c4c49022b84ee7255ce2ac9df19b53ef4b93944b8c71b3a14","observation_id":"b6ea7ef7-a838-49f3-be55-815f8c32ebdb","resolution":{"observed_at":"2026-08-06T13:17:11.689750Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.672331Z","title":null,"venue":null,"work_id":"bb0483f4-8f48-4446-a869-50323ab8cdab","year":2022},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.940042Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:bcabb102930960fc6faf5174ab1416516ed3b9e0d69a40ee5efadba521a49c53","observation_id":"4c0a719c-d977-4366-8227-dd49a6aec03d","resolution":{"observed_at":"2026-08-06T13:17:11.676538Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.657629Z","title":null,"venue":null,"work_id":"daa7eac4-186a-4c69-bad3-342def38d3ba","year":2021},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.944547Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:a1ae30113729c80fce477c8367fb4ee66292fd4f96976290467e3199f3bddfaf","observation_id":"e08d7488-d882-421d-b3b6-a76c858a7b1d","resolution":{"observed_at":"2026-08-06T13:17:11.661974Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.644441Z","title":"Bashir, C","venue":null,"work_id":"17066e4e-ca59-4ad8-9698-3a69eda77a52","year":2022},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.948714Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:29b9c44b4a16ea8564645beb442b55e4596b02f53d7939d789ffcc9491108dd7","observation_id":"2b0f24cd-e279-44ba-a86d-a85f53d40f22","resolution":{"observed_at":"2026-08-06T13:17:11.648438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.630085Z","title":"Berardi, A cross-country comparison of the building energy con- sumptions and their trends, Resources, Conservation and Recycling 123 (2017) 230–241","venue":null,"work_id":"2879c2a0-5cb8-4994-b16e-7bf692e14b40","year":2017},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.952561Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:c39a1ccb0ce5d22f4285a18a966f7b237ae4636128dd1cefcfca740484611367","observation_id":"9df90178-d48c-484a-be44-9d440b8691db","resolution":{"observed_at":"2026-08-06T13:17:11.634393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.616232Z","title":"Gupta, S","venue":null,"work_id":"8bf7ebef-d18b-4c69-89f8-1397782448ba","year":2023},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.956604Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:93cecc8fb5e98e3c9d151c472970409461dba0df365867b80f1ab38d2551aa7c","observation_id":"afb02fbf-46f1-4216-a47c-9e1f3dd22c8f","resolution":{"observed_at":"2026-08-06T13:17:11.620375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.603321Z","title":"Saeedi, M","venue":null,"work_id":"83c0aaf0-65fe-4bbf-9195-310da88e7394","year":2019},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.960541Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:cf8b48a3ede04da7cb8dda6bfb18f324abac5c5c531dd4798c8a89189e399416","observation_id":"5466889c-69b4-4914-87b6-d61f62758eab","resolution":{"observed_at":"2026-08-06T13:17:11.607500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.590612Z","title":"Zhang, Y","venue":null,"work_id":"774cf6d0-d8d5-4830-9718-c24922a12661","year":2020},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.965064Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:e29b36160dbe4306e85fb3befd0fd9e5faa796b2a4b6b22d163ae0b541b82d53","observation_id":"f6e151f1-fd3e-4096-b176-f2852ac4e8ee","resolution":{"observed_at":"2026-08-06T13:17:11.594799Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.576867Z","title":null,"venue":null,"work_id":"7df501b4-539e-4f30-9239-fb2bfe291a48","year":2020},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.969413Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:e07a447d832ddc8c6b3c5eb0335efc34c1051887f4e1dedf3895ac9dfa023858","observation_id":"b7a6dbfb-c565-484e-a955-19ca754e36ca","resolution":{"observed_at":"2026-08-06T13:17:11.580903Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.562922Z","title":"Arastehfar, M","venue":null,"work_id":"e901a82c-c24d-4806-b8be-856e550fc4b2","year":2022},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.973493Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:8996e3651d8325c94bee4f94615f5cb44e8af0b88a9e69d25899b87e227690ab","observation_id":"c78a4c28-8de5-4f9b-bdb0-504d2f958e45","resolution":{"observed_at":"2026-08-06T13:17:11.567172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.549186Z","title":null,"venue":null,"work_id":"50822f93-cd48-445c-9725-3d9aa51a5c1e","year":2021},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.977870Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:12d3703aca36826df1e48e57e3dcf1365a5c4ff5a2f435460ef8fde9bf5c4ed8","observation_id":"0a7cbde0-9a67-46de-babc-2218f02d0a34","resolution":{"observed_at":"2026-08-06T13:17:11.553412Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.536253Z","title":null,"venue":null,"work_id":"bdf82e46-b197-43b1-bc8b-bc1517ff51b0","year":2019},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.981896Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:d83ba3a359189612e90d2b9191faa64e0d16170c3a28fc824e50d522e6c946f9","observation_id":"2e21096f-a1e7-46bb-a560-5d5164ac2188","resolution":{"observed_at":"2026-08-06T13:17:11.540202Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.523021Z","title":null,"venue":null,"work_id":"abbbb9e4-9ce5-489e-8151-de9e798c2515","year":2023},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.986227Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:e4f6c7ecc48f07a26ffb77015270f5c2d6ccf11b4abd7ae3bb3c1f7d88aa5aa3","observation_id":"cb1912b6-6f59-4424-af8e-e01e60e22ff1","resolution":{"observed_at":"2026-08-06T13:17:11.526954Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.509427Z","title":null,"venue":null,"work_id":"1d4a2d82-0caf-46e8-8166-299175d57b9a","year":2018},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.990347Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:60eddc98b9cf8e4a729cec8ce26b553870966841f6b83937e19e6da4a67e6a2c","observation_id":"bc1ca933-d714-40bf-b506-d1eb08288d02","resolution":{"observed_at":"2026-08-06T13:17:11.513810Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.495363Z","title":null,"venue":null,"work_id":"629d83a3-390d-4402-9b2c-e5d42056d28e","year":2023},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.994592Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:1a6dcc4a5d9e2bd27cc87387d22a31a8080661ad503e0b5e2205e05a0cd70500","observation_id":"fb9306cd-46c1-4e29-a91f-e4e9a9d887cd","resolution":{"observed_at":"2026-08-06T13:17:11.499734Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.481655Z","title":null,"venue":null,"work_id":"90c9ecc0-b71e-4364-b109-653e3df75aa7","year":2017},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:10.998530Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:63f3c9b4a54d48a8f4b70ab555abbdb988a7b3e1069cde03e9f6298afdb7ec18","observation_id":"a7af114f-fee1-49c3-a08b-9d5b14103340","resolution":{"observed_at":"2026-08-06T13:17:11.485896Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.468267Z","title":"Gilmer, S","venue":null,"work_id":"ee6582a0-cb5d-4238-9de5-bf65a6176c59","year":2017},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.002566Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:fe2fdb78637fcf91b98f7e36a97c51e445c897b7d7e335de2a3d77875512c7d4","observation_id":"5ddb3ddc-9db5-4f1c-9483-24a05f5f052b","resolution":{"observed_at":"2026-08-06T13:17:11.472180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.04357","last_updated":"2017-08-14T23:47:02Z","snapshot_observed_at":"2026-07-06T05:55:18.328353Z","submitted_at":"2017-08-14T23:47:02Z","title":"Graph Classification via Deep Learning with Virtual Nodes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.04357","snapshot_observed_at":"2026-08-06T13:17:11.006765Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.006765Z"},"links":{"cited_paper":"/paper/1708.04357","citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:2b264addb75cc2b7c1b1aa4030ddd022c23cec0159398545713453f56a616b21","observation_id":"ff73aabe-8b1b-4b48-95eb-85cf71ba5832","resolution":{"observed_at":"2026-08-06T13:17:11.006765Z","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":"2026-08-06T13:17:11.454534Z","title":null,"venue":null,"work_id":"2500bbaf-47ed-4b9b-ad54-d7719e3cc827","year":2018},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.011674Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:85db60f07ee3a1a6b692e5dd3288d1aa9cf2c34f74dfd72ee042d425422eba59","observation_id":"00878fcf-d080-4a8e-b2e5-5c06ac526d71","resolution":{"observed_at":"2026-08-06T13:17:11.458565Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.440327Z","title":null,"venue":null,"work_id":"ace128f6-2442-4c15-a741-ec54cbbff7d0","year":2019},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.015829Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:a8d6e5ca050fe0732dc315e87deaeb45e8990cdc22626bd24cb0d1be195329da","observation_id":"cb81782c-94ba-4c86-b137-fee2c9e4a17e","resolution":{"observed_at":"2026-08-06T13:17:11.444804Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.426431Z","title":null,"venue":null,"work_id":"f47ccb4e-adc9-4428-9c9c-5bcbff16de3c","year":1990},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.019955Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:5505155c9b9006cd464184faa284a5cf1ebe276ee1abe2157e1d18c69b824b69","observation_id":"5de4d4a4-3e71-4141-8bc5-cd47059980e6","resolution":{"observed_at":"2026-08-06T13:17:11.430562Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.393435Z","title":"Hochreiter, J","venue":null,"work_id":"841da59a-9248-420b-bda5-8f3a14557709","year":1997},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.024405Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:6ba37dcc2f7a3b01d3630b89da35d3a72f994432321892ec05e558484b897b6a","observation_id":"8e0354a6-0b47-42ed-bfca-b5c43bd6f91a","resolution":{"observed_at":"2026-08-06T13:17:11.407649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.368260Z","title":null,"venue":null,"work_id":"a3e19427-0824-4600-98f4-b8f92adf86fb","year":2014},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.028432Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:12c84fc75fc43e3e5ef7790aecdbff4d362774f7f256b10470c1ed9fef3d4b6d","observation_id":"f283b0c6-1343-45dd-8075-0d435eb3d130","resolution":{"observed_at":"2026-08-06T13:17:11.378666Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.353122Z","title":"Vaswani, N","venue":null,"work_id":"ecff355e-7fff-44eb-9d56-27e5e1b81ecf","year":2017},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.032627Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:ba5c4cba26e2919ba294640358aa7c05eb9f4493a73742c5842393aca34ad68f","observation_id":"92291178-1d28-4129-9ddb-729c44decf5a","resolution":{"observed_at":"2026-08-06T13:17:11.357849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.338897Z","title":"Gross, F","venue":null,"work_id":"6ac09a4a-cca3-48f4-a957-c74a0a2fa43c","year":2005},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.036679Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:094fabd24db6af6ed79df6ea9c85431287c4e7aedef3b6cd8479cee6ff5bc5ad","observation_id":"bfaa37e2-f732-453e-8fbf-d094bd429d78","resolution":{"observed_at":"2026-08-06T13:17:11.342999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.324763Z","title":null,"venue":null,"work_id":"922fb91a-9329-4429-a38c-5605fc3c01dd","year":2016},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.040725Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:d505d2136d6f22b0dd7b8642534bf70f68fb0d8f62e4b652a3b6b38e979bf752","observation_id":"3600da8f-a9f9-4014-9b5a-4bfff2b18b56","resolution":{"observed_at":"2026-08-06T13:17:11.328823Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.310520Z","title":null,"venue":null,"work_id":"46d1a514-ff41-4cba-8e4e-3a281aca4777","year":2018},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.045236Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:a880ad803d4e6db7154195252e9bfedd097f7579e32c49fc08d6f294b50f543a","observation_id":"af17493c-faa4-409a-8a86-0a71fe10c3a7","resolution":{"observed_at":"2026-08-06T13:17:11.314753Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.049324Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.049324Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:7fb6482e6ed866d4c82c7f834a4f105e4e76af9200027f494479a09239ec478d","observation_id":"870fa09b-7b13-4185-9377-f440c43cfb0e","resolution":{"observed_at":"2026-08-06T13:17:11.049324Z","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":"2026-08-06T13:17:11.285294Z","title":"Miller, A","venue":null,"work_id":"c2d84e23-0ec7-49af-a0c3-768140f24c9e","year":2020},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.053911Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:ca721191266a493fb134b18cf42093e373b7e9ccb6caa34c2457ec59209bf091","observation_id":"36cdcf18-12e8-48c0-beba-f1a77dd0c8ea","resolution":{"observed_at":"2026-08-06T13:17:11.290435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.058489Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.058489Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:ff615f5a0c1bf9d507abc7ddaeeb3dd394cf745ee004b15b270144385ceae71b","observation_id":"f0ed1007-3eea-413d-8151-2fa38e19d4c4","resolution":{"observed_at":"2026-08-06T13:17:11.058489Z","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":"2026-08-06T13:17:11.258907Z","title":"Platt, Sequential minimal optimization: A fast algorithm for training support vector machines (1998)","venue":null,"work_id":"1bc544e1-5b5a-445b-b21e-d5120d1ca100","year":1998},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.062470Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:a9289f02f714250147a03ae5df7de34df9d05bfeb244edc1a964f8f91fe50fbe","observation_id":"aefe445e-423b-49c7-8e79-1f0a682e84f4","resolution":{"observed_at":"2026-08-06T13:17:11.263322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.242317Z","title":"Drucker, C","venue":null,"work_id":"6300cf9d-1694-42fe-9314-064cc38b6d09","year":1996},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.066920Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:d6d852ff669fe32940dee4fcea79aaa860f520ca6cecd5f8b5c8663613b21f96","observation_id":"d7fa98c1-fc5d-40ff-b647-ac0f0f135411","resolution":{"observed_at":"2026-08-06T13:17:11.247315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.227540Z","title":null,"venue":null,"work_id":"3dc764a2-41fc-4f36-ae2e-b1ac131f4994","year":null},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.070968Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:62777e2c46f96386361d22c188352fd0513f3cef85b275cbf9d36087b4c6750e","observation_id":"dca78234-3fb3-4d8d-abb7-d91787b904f1","resolution":{"observed_at":"2026-08-06T13:17:11.231724Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.212165Z","title":"https://pytorch.org/","venue":null,"work_id":"f0574a3c-ced8-4ae9-9c92-c0ffc8b4022c","year":2025},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.079719Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:d0ced919a237a16577a2d55cae530e7de41f365fda36f43e432382727ca7caf2","observation_id":"598d2b28-8e9e-404e-a988-28821662fdd4","resolution":{"observed_at":"2026-08-06T13:17:11.216630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-06T13:17:11.084154Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.084154Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:36fc879eb9b81ec1ac3db7e25d6bca76e1cde8a4b56eac97935dcdf6998b808f","observation_id":"342d5de6-2ae4-4087-a4fb-d16dd0094f33","resolution":{"observed_at":"2026-08-06T13:17:11.084154Z","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":"2026-08-06T13:17:11.197018Z","title":null,"venue":null,"work_id":"d3e0fcaa-63a9-4809-b9db-a45af92c3129","year":1987},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.088916Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:28ba843704d106b645a4fd72613d6f8c82fddfb3d86e2ac57af27e5a6ed34560","observation_id":"df32b6a5-c949-468e-9c79-268e5f8e3126","resolution":{"observed_at":"2026-08-06T13:17:11.201374Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T13:17:11.182135Z","title":"Van der Maaten, G","venue":null,"work_id":"9fb546fe-0e19-4870-9b31-2ea91c417aef","year":2008},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.093376Z"},"links":{"citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:67338bc7597710efae3f87ac659384f263c8477b83ce54c35524044d1e6daecf","observation_id":"aeded86d-3de1-4a77-af99-84b45fb1dbac","resolution":{"observed_at":"2026-08-06T13:17:11.186659Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.11650","last_updated":"2020-05-24T04:02:18Z","snapshot_observed_at":"2026-08-06T17:14:25.237071Z","submitted_at":"2020-05-24T04:02:18Z","title":"Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks","version":1},"cited_work":{"arxiv_id":"2005.11650","doi":null,"metadata_source":"pith","pith_arxiv_id":"2005.11650","snapshot_observed_at":"2026-08-06T13:17:11.147128Z","title":"Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks","venue":"cs.LG","work_id":"86a00d43-28b9-4480-8567-09fa3440d0ff","year":2020},"citing_paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:11.075031Z"},"links":{"cited_paper":"/paper/2005.11650","citing_paper":"/paper/2507.20838"},"observation_digest":"sha256:7cb991ce5b4256a6161f41040717d65103552c712334b03148149e3d9b43d105","observation_id":"99954ed9-0846-4c29-93e1-d4f01ebd4e15","resolution":{"observed_at":"2026-08-06T13:17:11.153836Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.20838","last_updated":"2025-07-28T13:47:36Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T13:17:10.349721Z","submitted_at":"2025-07-28T13:47:36Z","title":"BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":28,"verified_exact":1,"verified_fuzzy":17},"total_outbound_references":46},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.20838."}