{"as_of":"2026-08-07T08:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:db97793a1a430a5110c2173200151618af7f92ed4f2bc5df86f697041283ab85","coverage":[{"denominator":51,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T19:21:47.532362Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"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/2607.04414/citation-record","integrity":"/paper/2607.04414/integrity","json":"/paper/2607.04414/citation-record.json","paper":"/paper/2607.04414"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/aaai.v40i34.40088","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence , volume =","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","work_id":"c6ff7f74-9dc5-410f-bef8-ddc15c070177","year":2026},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:f04e3bbf4bd9fcf89df71efb965bd979068fbf397ae3f8e2a1a648018c7cf49a","observation_id":"4b87b85d-7b67-41e8-a09c-83a14189f80f","resolution":{"observed_at":"2026-07-11T19:28:13.052742Z","resolver_source":"doi","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":"2026-07-12T08:49:28.141654+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T08:49:28.141654+00:00","source":"openalex_status_cache"},{"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":"2026-07-11T19:21:47.532362Z","title":"The Lancet , volume=","venue":null,"work_id":null,"year":1990},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:7dd73fa016a51c7d96cbe4c6c34f9a989373c16fa9313aaf505ade64b5cbb85b","observation_id":"5ba1d8a5-d26f-4596-aa6e-ad1d10da0b33","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Transactions on Industrial Electronics , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:469bfd92b25ea239d6ed31161ab06a4196e1db1272b4ff4cdbf96ee27cbc088c","observation_id":"67dccf76-6c6e-4d12-9f21-46f2aab74ca5","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"and Kuhar, Peter and Hughes, J","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:9edbe514186bae6f59e6fe2c5089e75d6eb8086d5b7eef1d9f2b51bc9d54abf8","observation_id":"5a91e6a1-77d8-49dd-9418-7b94d04ceede","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"and Ponnapalli, Prasad V","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:48af40a39c00ddd646ad194d27a44aaa0f0a78e9cb59ffb909b3c41978b7265c","observation_id":"63251673-40cc-4015-a914-87f84e3056b0","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"and Abbott, Derek and Lim, Kenneth and Ward, Rabab , title =","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:b7c49129214b520d63b455c865fb5b35de19d34ed5825932365151b76c5ac784","observation_id":"39e2dd0a-9145-46fd-8feb-7c52dfffcc11","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Journal of Biomedical and Health Informatics ,year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:6fc595476a4e11166fb5e17fc5c3d2bd143759a313b69e915b6d9b52d3bb8e5b","observation_id":"0a13f422-6074-4d71-b212-63e63bf2efb0","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Journal of Biomedical Informatics , volume =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:f5fad2782fc1f8aaaa7cf1b2cd0da33c3aa9b3f023e57845497458e73246c4aa","observation_id":"31e13bc8-07b7-4d02-b99a-1b26cbadd78b","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Transactions on Neural Networks and Learning Systems , volume =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:02ab8a68be3a109450195735e1425ec3271e1320e2bafa3359751e76ef7a0633","observation_id":"e3fb1bf4-6160-45d7-bf19-c317aede357a","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Journal of Biomedical and Health Informatics , volume =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:733b1a60bbb9b0fd06e78b27d6c04a2430c8f0d9b7aef40bec38771870c25ade","observation_id":"de9f882b-d63c-4201-b58f-a13173d63972","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Transactions on Industrial Informatics , volume =","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:6b0a506eb5ab12d26116a436b709fa9f477a5e9cc2aee3177f0e9f5fb4abde21","observation_id":"54412362-009e-40e0-b82c-d57fb856fc79","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Biomedical Signal Processing and Control , volume =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:293df336be3c2393190dddaca518f3489c635e8a7861a06de1f82eb5ce0a6efb","observation_id":"05250df5-d462-40da-8177-f6a1563ef8f4","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Transactions on Consumer Electronics , volume =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:80febd1636bbb8b7c97188b262ecab98531f7583ed771ab1d3327d736b55f013","observation_id":"58571733-db35-4aa8-b2fd-3d25a4d471f2","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Journal of Biomedical and Health Informatics , volume =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:3b9000cbd0bcb976639863f6c61f14b203ae910af85e6fc0665c22fe5304b975","observation_id":"23393c67-68e2-4ea8-b34e-4ca01f98689d","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Biomedical Signal Processing and Control , volume =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:9c11c6f6a3caaee7553e32c5325a95981a7a4f12499ab37599b7accc95e53531","observation_id":"2f2c5bee-d215-4520-b732-73023ac913e6","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Transactions on Biomedical Circuits and Systems , volume =","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:4812b60bed82c0afeb87bc3092beb2662be05a0dfe02896406884468f2bf8c77","observation_id":"8abfcd16-9f21-4a3e-997c-de9cd8e7233c","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Sensors , volume =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:02289877a7d20b54cf0f6d2ab1d67cfb58e4a4f8300e704928931a9a6c636eb8","observation_id":"9afa60af-af54-4a8e-8911-67ef885ba68b","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Biomedical Signal Processing and Control , volume =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:12e27634e873826a75ec3da42d0604f85ca2e9134ca2bfe7ec8ad463fa6083fb","observation_id":"3d7574c8-47a8-474e-a725-bc088f263699","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Thirty-Eighth AAAI Conference on Artificial Intelligence,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:bd391a76201282965c94ca74326ecd8101af58ca6712d4ff83ddf3a423367793","observation_id":"f37c1cfd-3a03-407c-9eaa-50ac95fb43cd","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Transactions on Pattern Analysis and Machine Intelligence ,year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:47a5b7fe2e8a5ec1587ff418cb8714e2e7b54074eabe7fe2ad068ceb087f607b","observation_id":"07dc183b-b872-40b0-bc7e-80f98f4acfa6","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Applied Sciences , volume =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:bdf380097f67f27de39086b835d8429291ecb4ee234835bae00f9b2485b0f5bf","observation_id":"fa400b62-45b9-47a3-b973-6bf6a7ff9b61","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Advances in Neural Information Processing Systems , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:7d699f11bb9d17c53c4c06225864646648b06e5e62148e69b8709d1017d4db89","observation_id":"d23954d2-0d6c-443a-9ebf-316ce0fdf68e","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Scientific Reports , volume =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:a4904542158214e931e0767cd7f466d97fe24ee127d9b8c9870dbbe487904c29","observation_id":"59813f9b-9d29-46e9-bdec-b2851894eb76","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Frontiers in Digital Health , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:6766948271a48c6ef09a974e83e39b1d00988f9cb33b43d60ae4c74825e2a282","observation_id":"229ac051-5b82-4d5e-b61b-e6c9d31fa992","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"and Alex, Zachariah C","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:d40dce54cb6c574310f81a12dcffbd94938a2b4da7e8c74c6eba9c26bdac69c1","observation_id":"7489b5a7-51f8-4c67-b109-ac6d58f69071","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"2017 , publisher=","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:386da5351dbb5b7bebb3ed18d601a28a5fdb7c7d6bf822207d3bebe4d64808e0","observation_id":"4d14d0fa-fe65-4cee-a911-56647c96481c","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":", title =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:e58de37f69b4fac13513988be12f805d50ffa98ade665bb4404bff167c0e3eb8","observation_id":"75e9c20e-2f3a-48f1-a6dc-81812e6ddb29","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Sensors Journal , volume =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:950073d474aa538b485ca955e7c6d171203e1e6f9983cc195cca8fcfc759bfaa","observation_id":"ad2379a3-43f4-4562-953c-c595eed08f36","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"2024 IEEE International Symposium on Circuits and Systems (ISCAS) , year =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:d037603e79843fcebb650a56138dd5374ccf33010f0d811288550393b7bf8f07","observation_id":"cf42d07b-f2d9-4d63-913d-fc2d90847e81","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Journal of Biomedical and Health Informatics , volume =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:43ffd4194ce2e0667662a6dee9e607fec2a1b623107d52c500223ea28415e2a0","observation_id":"e4df8a3a-f610-46f9-8b11-02d77978601b","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","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":"2024.106902","doi":"10.1016/j.bspc.2024.106902","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Biomedical Signal Processing and Control , volume =","venue":"Biomedical Signal Processing and Control","work_id":"1a4f1688-a5fc-4fd8-96f5-726e796256a4","year":2025},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:cdf0da8a1c2c91d40c4e544d7acc89cff4110e6786a0ef0e8e73b43e5f499b9a","observation_id":"d6e7e11a-ed5b-4df2-9157-f504fe248224","resolution":{"observed_at":"2026-07-11T19:28:13.047439Z","resolver_source":"arxiv_id","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":"2026-07-12T08:49:28.461948+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T08:49:28.461948+00:00","source":"openalex_status_cache"},{"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":"2026-07-11T19:21:47.532362Z","title":"Cardiovascular Diabetology , volume =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:c4f2271866683a0477c96b1a1e10b15f1c60e21885fbf83bb4d612810ff42455","observation_id":"c802992f-7e18-4d97-a872-59363929daed","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"and Tuytelaars, Tinne and Tolias, Andreas S","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:acdf0d6ad4489c16faff57c54dd3786cec9d985a10efc4e129e3667b654b362c","observation_id":"20c52775-a028-4456-b8a4-e8bd3de8fe18","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Neural Networks , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:7b8f654519bf632b4dc8d46109bedcd66f96ff225ac1f7837154725e2037b2ec","observation_id":"1444cf67-fbb6-4ed6-a520-7abbd202d774","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:02d54b4132d9756fa16b687d71dbb8c17fdfa940a7238417d0513c301781c7dd","observation_id":"389c6308-9f69-4f74-8ef8-54825efefb4c","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:55a7f47142744366141a8ae0ea341515962fbc80ba2acddb15620a3a9942e315","observation_id":"bc4c73a8-084c-4eca-ad86-909942b58609","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Kudithipudi and M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:8cb6c236a8a18e58b7a60b357e281431ae8114889b7251336b61875f5dfc5bb0","observation_id":"1004dd17-82a9-4fa4-b979-7712fa30a3ff","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Scientific Data , volume =","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:9084ee5b447b09adf608289586ca371b9f5977aec7db7d94db19ba5a075f86f6","observation_id":"b5fd6e17-03f0-4979-87ff-5581d13b1062","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"and Weber, Jonathan and Webb, Geoffrey I","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:fe6636637754606b39b7ed0da1fcedb1c9a193fdfae55b334b147bff4fe7c552","observation_id":"510108a2-dc97-46c4-b115-11e5fb113b54","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"and Cox, Daniel and Gonder-Frederick, Linda A","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:4bd2ce60c019cb179cfa1a2c38629bb33cfbd7ba68754da13e4a105d70ab5b90","observation_id":"f69986d5-247e-41d1-b87e-77ba3c985547","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Scientific Reports , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:545142655d7590a3f7a82a514a34d161566c06917c6ceb2198fc95c7ca31478b","observation_id":"8e611c78-cdf3-4059-8c91-fd0f5a78a69b","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Biomedical Signal Processing and Control , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:211317a5274801199e00ccacf65f9010a89ba6bbd714e4615dcf679f270406a0","observation_id":"ba98ee22-bf0d-439e-9e65-e1d961a983f1","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Nature Machine Intelligence , volume =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:f9a82916f170f299b6b374a0b4647fa45c7b4d02a6fb32be17df3a5cab4d3f7c","observation_id":"2ecd9a80-034f-493c-8889-0d0853c60186","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:471ed442a5fa074e03f0bb41369071cc383c61e0db58a88f740dda112a6cbe0a","observation_id":"8caf3c82-1182-4bad-bdb8-6aa54cfa72d5","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Pattern Recognition , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:d59bf85a1ccd9cd8114dcfb9b48ea084d805d72d216ad6a18421dff8d26761e0","observation_id":"a41439a1-d73c-488c-a2e0-8b995832dcc2","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Bioengineering , volume=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:cb7875f95a128deddfe415f23ce8b59f87add4c024bdee97f7ce330762c53dff","observation_id":"d9b20237-f29a-4b05-b079-99e4417ad49b","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"IEEE Transactions on Biomedical Engineering , volume=","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:29ae09bda2039970d37152230f731afb846bc099ff53eb1b4a91c3e2ef7099bb","observation_id":"1ef5bf39-1f47-4e6f-9cc9-0e2ea7443271","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"2023 , doi =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:3ff20983ac5ace5bcc5217e3698c019da7cc964586c86512181ac7b574ae3235","observation_id":"42a44a2f-6411-4dae-99ee-46c842113eab","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Nature , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:d85c85ac7e6a55b91de5eed1e52eb683906ce512f01ab5cee64e50130a86a960","observation_id":"0ff42851-615f-43d3-9fdf-9129b3ee1ab6","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"Frontiers in Public Health , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:8400459a108e3520ade1d3f71490cf8efebf22ac182c61dc81cd5da0b6f7dcb4","observation_id":"6d493043-7477-4fa4-8f15-cd76fe2c1e17","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:21:47.532362Z","title":"The Shapley Value in Machine Learning , booktitle =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-07-11T19:21:47.532362Z"},"links":{"citing_paper":"/paper/2607.04414"},"observation_digest":"sha256:b6c35b5d3e702f83578324bfc470f84a43c5dc8aa3d5b00212884c2aef8e610e","observation_id":"f2de4ba2-001a-4ce8-be6a-bf22eb03c517","resolution":{"observed_at":"2026-07-11T19:21:47.532362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.04414","last_updated":"2026-07-05T17:08:32Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-07-11T19:21:38.811928Z","submitted_at":"2026-07-05T17:08:32Z","title":"Non-invasive Blood Glucose Estimation from Wearable Physiological Signals"},"reference_resolution":{"displayed":51,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":49,"verified_exact":2,"verified_fuzzy":0},"total_outbound_references":51},"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 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2607.04414."}