{"as_of":"2026-08-22T19:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d06c341aef7ec432ee38e5bcba7840d0577f15a4137767ae57cc13f3aec9d8f4","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T11:30:37.880500Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:22:35.603147Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-16T12:22:35.696439Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"cited_work":{"arxiv_id":"2411.18141","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.18141","snapshot_observed_at":"2026-08-16T12:22:35.696439Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","venue":"quant-ph","work_id":"8170c166-dc70-4207-be24-0006de44e8dc","year":2024},"citing_paper":{"arxiv_id":"2504.13041","last_updated":"2025-04-17T15:55:37Z","snapshot_observed_at":"2026-08-21T15:19:50.907193Z","submitted_at":"2025-04-17T15:55:37Z","title":"QI-MPC: A Hybrid Quantum-Inspired Model Predictive Control for Learning Optimal Policies","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T12:22:35.603147Z"},"links":{"cited_paper":"/paper/2411.18141","citing_paper":"/paper/2504.13041"},"observation_digest":"sha256:31deb04d2e25342369f5c68dec9b1f4cdd720ead38f85645d8ef8fb222d19d0d","observation_id":"3b11fd29-989d-4792-addf-5861dacab478","resolution":{"observed_at":"2026-08-16T12:22:35.701115Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.18141/citation-record","integrity":"/paper/2411.18141/integrity","json":"/paper/2411.18141/citation-record.json","paper":"/paper/2411.18141"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:30:38.233823Z","title":"Water Quality Research Journal 53(1), 3–13 (2018)","venue":null,"work_id":"d9a59d99-dee7-43d8-88d8-7996b26132ad","year":2018},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.773361Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:d7fa5806e8796eee521ae8186e74c6b904d51c9e7d2e04218c4df0b0b69bd512","observation_id":"0441e9b3-3726-4e1a-b59b-f2de1bb82990","resolution":{"observed_at":"2026-08-12T11:30:38.236646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.225766Z","title":"Journal of Hydrology 578, 124084 (2019)","venue":null,"work_id":"6af17408-a12a-469c-b97e-b29a6b8dd410","year":2019},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.777229Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:0be6237a1e127792cfd1c376633b4109f4ce7db2a658e898e70799107b1e311c","observation_id":"43488ab1-e9f4-4fff-beb0-3cc1579fd22c","resolution":{"observed_at":"2026-08-12T11:30:38.228442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.217894Z","title":"Eco- Environment & Health 1(2), 107–116 (2022)","venue":null,"work_id":"04672577-b9b3-41d7-a23c-00a4f41ee05d","year":2022},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.780737Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:ff5661c8bb923dec189243144e1ff0887ae45fc7a393d5f641b1da3aab010a4d","observation_id":"d365020c-7d2d-4b92-bb9d-29df4e126132","resolution":{"observed_at":"2026-08-12T11:30:38.220601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.208860Z","title":"Journal of Hydrology 585, 124670 (2020)","venue":null,"work_id":"a4ea6050-63ac-4a43-b9b2-d0e34e8ff72f","year":2020},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.784653Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:b3444b4943c6f392bc436257b83d69bc5f4d25ab3460e9f694adf8eed36e6b5c","observation_id":"d7beea5c-3994-4498-ae75-79bed7afcbbd","resolution":{"observed_at":"2026-08-12T11:30:38.212098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.199621Z","title":"Modeling Earth Systems and Environment 8(2), 2793–2801 (2022)","venue":null,"work_id":"85250e51-c45d-4caa-a74e-25bf9fabb905","year":2022},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.788161Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:cb3c8e016613d9e906b010fde1dde615ccf1ae8cac8604ede4d8d926e03c3694","observation_id":"fb43197d-5e01-4683-91ec-170fa6a94f2a","resolution":{"observed_at":"2026-08-12T11:30:38.203076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.190741Z","title":"Journal of Cleaner Production 406, 136885 (2023)","venue":null,"work_id":"108d10f0-f359-4083-b68a-89e55d9e30b6","year":2023},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.791396Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:53c05e52bdcc4bc7783a0c4fbc165d46698b48d6b3bd8aaff39caf63e74c5f32","observation_id":"86a9d592-0a5e-4fde-adac-dd8c510eeb95","resolution":{"observed_at":"2026-08-12T11:30:38.193832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.181638Z","title":"Water 14(19), 2939 (2022)","venue":null,"work_id":"494a3778-6f2d-4510-a45a-afdd1e8dd4d2","year":2022},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.795003Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:8349f205300c6213e5cadcf46c9ae714d9c5eaabeb1a80becb8d99356deec77a","observation_id":"a090838c-7d4f-48ea-b415-96731e474d09","resolution":{"observed_at":"2026-08-12T11:30:38.185039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.172968Z","title":"Water 14(21), 3359 (2022) 11","venue":null,"work_id":"2b1cfeaa-5f35-4f89-b457-69c460ac7cc2","year":2022},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.798222Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:111bb2e5660aa24ea105e5869745c69b2f6c4fa709bf5cc62225e606479ffc2f","observation_id":"4fb2dde1-8a64-4e33-9164-2b2c1014a981","resolution":{"observed_at":"2026-08-12T11:30:38.176056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.162499Z","title":"International Journal of Quantum Information 22(02), 2350044 (2024)","venue":null,"work_id":"bf1c38b3-14df-4bfe-9609-64f1ed8f6cf4","year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.801402Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:20fb4cc513904294c5320c825abbc9b0fe78b95c988135effd3b9f0a1f5c7fec","observation_id":"d5846ee2-0728-4dc4-9c63-b7b71243a755","resolution":{"observed_at":"2026-08-12T11:30:38.165898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.153460Z","title":"Quantum Machine Intelligence 6(1), 7 (2024)","venue":null,"work_id":"5341ef0a-6eed-4f5a-880d-c101e4b13319","year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.804388Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:b9255928df0784fda41c1b75183208ab2d9d8816dcdf60af093dfa7755155203","observation_id":"5e094d79-ac3a-497c-b807-1ba7dd6b95e0","resolution":{"observed_at":"2026-08-12T11:30:38.156633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.01203","last_updated":"2022-08-02T02:08:52Z","snapshot_observed_at":"2026-08-21T06:12:15.377842Z","submitted_at":"2022-08-02T02:08:52Z","title":"Unsupervised quantum machine learning for fraud detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.01203","snapshot_observed_at":"2026-08-12T11:30:37.807396Z","title":"arXiv preprint arXiv:2208.01203 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.807396Z"},"links":{"cited_paper":"/paper/2208.01203","citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:2edf0ca6bcf7a2c4c15cfe6dc1d0ed76e24e2f0e8b8fe6906518cfaf12eaec1d","observation_id":"71efa9e5-3263-4cc7-8865-24e9ccef9251","resolution":{"observed_at":"2026-08-12T11:30:37.807396Z","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":"2026-08-12T11:30:38.144424Z","title":"IEEE Access 10, 75908–75917 (2022)","venue":null,"work_id":"ae68f9c5-9de7-4ccc-b151-38337c7bb584","year":2022},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.810932Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:032f4ac443df88d0cf515db450af534091d337f868a1f6bb3bd1dbfc38eb91fc","observation_id":"41dec2d6-9ef0-4add-85c1-ce153b5d5968","resolution":{"observed_at":"2026-08-12T11:30:38.147467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.135339Z","title":"Physical Review A 97(4), 042315 (2018)","venue":null,"work_id":"9bacd3af-c4dc-4395-b949-a8a965075e40","year":2018},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.813943Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:a5c1f4cd30d5f19b44d724772d7f9fd2136eb8167d5d31c12268cf24951be371","observation_id":"8c1078fd-0fff-4e4d-9234-c22aae576ca6","resolution":{"observed_at":"2026-08-12T11:30:38.138484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.125566Z","title":"Journal of chemical information and modeling 61(6), 2641–2647 (2021)","venue":null,"work_id":"840cab94-4c6a-4f7e-9610-1464ba82329a","year":2021},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.817154Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:c87283aa8c8cf296b3239637fa1d5ddeb61c2d5115a6a12c9c04afa528c3ffe0","observation_id":"c3d61eb2-3506-4115-a6d0-87a3eb671b69","resolution":{"observed_at":"2026-08-12T11:30:38.129072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.116110Z","title":"Machine Learning: Science and Technology 4(1), 015023 (2023)","venue":null,"work_id":"50407b4a-806b-49eb-8584-1b64d784993f","year":2023},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.820232Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:c7406ff7c9b9b8bd5836440ab29aa3cb851a408d78806eada48dd3e653c3331f","observation_id":"044fbb00-98ad-4fd7-b934-0901f2352ff2","resolution":{"observed_at":"2026-08-12T11:30:38.119372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.107439Z","title":"In: 2021 58th ACM/IEEE Design Automation Conference (DAC), pp","venue":null,"work_id":"e133a040-ec02-44fc-aab8-ea0692e5ad09","year":2021},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.823228Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:ccc76051a10657d1f71f758ba69dd2262f0b2cd9c449b00e255b8618abd03fb1","observation_id":"c04a8672-b137-4f23-83e2-1b9ee149d238","resolution":{"observed_at":"2026-08-12T11:30:38.110458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.098615Z","title":"Journal of Chemical Information and Modeling 63(21), 6476–6486 (2023)","venue":null,"work_id":"1a3d16f6-f9f4-4ed8-9b35-862ce030f3c3","year":2023},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.825878Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:6e687357803454b7b3ede416e1e6fc199e67723e739ca84bf4a399c3927baf01","observation_id":"449bd524-352a-4b61-9323-354096130c32","resolution":{"observed_at":"2026-08-12T11:30:38.101755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.088647Z","title":"Physical Chemistry Chemical Physics 24(18), 10775–10783 (2022)","venue":null,"work_id":"759fa121-f3be-4ade-bb7d-5e785d20066b","year":2022},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.828455Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:24e359d312cb8f0cd4dfa0eaeab428971a507cde98a491767c2182a10cbb7d20","observation_id":"d46449db-6e7c-4347-b6d3-464a0381cf14","resolution":{"observed_at":"2026-08-12T11:30:38.092134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.078001Z","title":"Handbook of Materials Modeling: Methods: Theory and Modeling, 1883–1909 (2020)","venue":null,"work_id":"816e4ad5-77a8-4769-8227-dbc75f4661a1","year":2020},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.831083Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:f84883e3e6d53bc8ddb6cd57c7de39aff473ffde6b01b16385ef2d67e478cfe8","observation_id":"5efa1944-a6b3-42c3-8c87-98213d0e241b","resolution":{"observed_at":"2026-08-12T11:30:38.081428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.068365Z","title":"Nature communications 9(1), 4195 (2018)","venue":null,"work_id":"bba161d5-a0ea-400a-8998-fe5832780144","year":2018},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.834912Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:61cb55353c6ddd2650679cd950f3a87fc7d313452f9ea9b507d2248d01e01617","observation_id":"f7f608df-ff96-4234-a72d-38f815a21fae","resolution":{"observed_at":"2026-08-12T11:30:38.071650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.07902","last_updated":"2023-05-13T12:02:05Z","snapshot_observed_at":"2026-08-18T01:12:17.825511Z","submitted_at":"2023-05-13T12:02:05Z","title":"Electronic Structure Calculations using Quantum Computing","version":1},"cited_work":{"arxiv_id":"2305.07902","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.07902","snapshot_observed_at":"2026-08-12T11:30:37.964621Z","title":"Electronic Structure Calculations using Quantum Computing","venue":"quant-ph","work_id":"7e1dd257-f78d-49ec-a313-c6fe5d4a2f85","year":2023},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.837437Z"},"links":{"cited_paper":"/paper/2305.07902","citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:85972e2018313f2c1acad0610ec0d16c701f97ccb4659986a9e74790ad8ee19c","observation_id":"c490cda5-7697-4158-9cba-d5d0cfb5c69e","resolution":{"observed_at":"2026-08-12T11:30:37.968103Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.058815Z","title":"The Journal of Physical Chemistry Letters 14(31), 6940–6947 (2023)","venue":null,"work_id":"99237024-cbc8-4e9a-b55e-69edef9569be","year":2023},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.840575Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:592d11732facccf7f5ddf1b5ae323ff124e22ff4e52cd13075892390b6eb78a5","observation_id":"eca229ea-f568-422f-ac65-04cb3765342b","resolution":{"observed_at":"2026-08-12T11:30:38.062486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.18731","last_updated":"2024-07-26T13:34:26Z","snapshot_observed_at":"2026-08-16T13:30:47.070503Z","submitted_at":"2024-07-26T13:34:26Z","title":"Exploring Quantum Active Learning for Materials Design and Discovery","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.18731","snapshot_observed_at":"2026-08-12T11:30:37.843403Z","title":"arXiv preprint arXiv:2407.18731 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.843403Z"},"links":{"cited_paper":"/paper/2407.18731","citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:bf1c3d1a218510b97f773b705392200a9762184b706ab5a5201cdf55027e9fc8","observation_id":"de0c0689-c859-4203-b7f7-0ec51e7aa8c4","resolution":{"observed_at":"2026-08-12T11:30:37.843403Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18989","last_updated":"2024-05-29T11:09:16Z","snapshot_observed_at":"2026-08-18T01:12:14.393527Z","submitted_at":"2024-05-29T11:09:16Z","title":"Classification analysis of transition-metal chalcogenides and oxides using quantum machine learning","version":1},"cited_work":{"arxiv_id":"2405.18989","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.18989","snapshot_observed_at":"2026-08-12T11:30:37.942103Z","title":"Classification analysis of transition-metal chalcogenides and oxides using quantum machine learning","venue":"cond-mat.mtrl-sci","work_id":"27d37a00-44e9-4165-9e9c-74b23af45e6f","year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.846609Z"},"links":{"cited_paper":"/paper/2405.18989","citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:b9eed454349f6a5b899aad1698af88739f446eebc3f4a89cba1cb377b709cf1c","observation_id":"9b058e99-7164-49c2-97ed-077a18247425","resolution":{"observed_at":"2026-08-12T11:30:37.945616Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.047711Z","title":"Springer, ??? (2018)","venue":null,"work_id":"f4b1fca4-85d0-41ee-8b5b-513e9c34eb0c","year":2018},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.849968Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:2a14c4565d8cd4c8dff865a27c3e3602b14904959fea96eb9029669041496c3a","observation_id":"91345b81-8406-4ce8-ae6c-732c24cdc845","resolution":{"observed_at":"2026-08-12T11:30:38.051625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.038035Z","title":null,"venue":null,"work_id":"b5d74859-c2a5-40ac-89b6-4bb2a8d12b60","year":null},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.852740Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:68e9d15fd401013f71e1572f2cc98b93da3170471b4a9e8dc7bf40d6ce9912fa","observation_id":"01d09bb5-53d5-4abc-b9cb-2ea7ddb5c8e8","resolution":{"observed_at":"2026-08-12T11:30:38.041311Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.022447Z","title":"Durban’s Climate Gamble, 75–116 (2011)","venue":null,"work_id":"787bc635-efe7-44fa-a64f-4a277f855456","year":2011},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.859156Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:8579daa4e59568967927f8e42377b3068f404196d932f4d64d452908801c73ad","observation_id":"e762fa93-2eaf-40cd-9299-167b8c99cff1","resolution":{"observed_at":"2026-08-12T11:30:38.025747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.012114Z","title":"Journal of Contemporary African Studies 37(4), 275–293 (2019)","venue":null,"work_id":"aa4665f7-c894-4f9d-838d-8eddfb517c78","year":2019},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.862087Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:97d4fbdce4324645346e6fa85a33e4ae51fd464050e4341710705a67cde11628","observation_id":"bc1e90c3-4f09-419a-be06-ffbc73ee7ece","resolution":{"observed_at":"2026-08-12T11:30:38.015859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:38.002326Z","title":"Mediterr","venue":null,"work_id":"7a029606-9c3e-40f0-8f60-39e0c95cbabf","year":2014},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.864802Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:dd8eefd760d5b3178273ac3e982123ac4c0d1cf9f6cba2f5b3a70b67cbcac507","observation_id":"c474e666-0118-4916-b2a3-40dfa9a57ef4","resolution":{"observed_at":"2026-08-12T11:30:38.005624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01001","last_updated":"2024-07-01T06:31:41Z","snapshot_observed_at":"2026-08-18T01:12:21.305182Z","submitted_at":"2024-07-01T06:31:41Z","title":"Flood Prediction Using Classical and Quantum Machine Learning Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01001","snapshot_observed_at":"2026-08-12T11:30:37.867747Z","title":"arXiv preprint arXiv:2407.01001 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.867747Z"},"links":{"cited_paper":"/paper/2407.01001","citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:c6bfb84d0ddb314a013baf681b89a792af1d0fae3bf60f3dfb791eb333d6a140","observation_id":"0fd369a0-932d-454f-8b3e-4bfdbda60513","resolution":{"observed_at":"2026-08-12T11:30:37.867747Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08617","last_updated":"2024-07-11T15:56:00Z","snapshot_observed_at":"2026-08-20T12:58:08.022805Z","submitted_at":"2024-07-11T15:56:00Z","title":"Quantum-Train Long Short-Term Memory: Application on Flood Prediction Problem","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08617","snapshot_observed_at":"2026-08-12T11:30:37.870904Z","title":"arXiv preprint arXiv:2407.08617 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.870904Z"},"links":{"cited_paper":"/paper/2407.08617","citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:22de60c523c1beb71317a5e7f69df71e626d4f45e8812c10282267b8458f586d","observation_id":"6efcbcf9-ae44-4d75-8be5-e281a10c5756","resolution":{"observed_at":"2026-08-12T11:30:37.870904Z","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":"2026-08-12T11:30:37.992593Z","title":"Journal of Computers and Intelligent Systems 3(1), 01–15 (2025)","venue":null,"work_id":"63d52ce9-790c-4533-8ff0-f693b7d87457","year":2025},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.874247Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:7f7659445bcc6111966821ab6e49e5c54a2bcff51e9c55cf8dbc7ebac814d295","observation_id":"c74dee20-84e5-47ef-ac9b-0d0c67d72f06","resolution":{"observed_at":"2026-08-12T11:30:37.995856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:37.983424Z","title":"Computers 13(8), 191 (2024)","venue":null,"work_id":"b70f2020-8006-49f8-9a0b-db9a05646b67","year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.877628Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:67b7185ed91d416ff84d7e9e47cc666748f0604b2ad6848d42ff71c2b2461132","observation_id":"71bbf972-83e8-4aa6-b27a-22d0baa2e2e0","resolution":{"observed_at":"2026-08-12T11:30:37.986701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04635","last_updated":"2024-11-07T11:46:48Z","snapshot_observed_at":"2026-08-19T15:31:24.648687Z","submitted_at":"2024-11-07T11:46:48Z","title":"Cybercrime Prediction via Geographically Weighted Learning","version":1},"cited_work":{"arxiv_id":"2411.04635","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.04635","snapshot_observed_at":"2026-08-12T11:30:37.908447Z","title":"Cybercrime Prediction via Geographically Weighted Learning","venue":"cs.LG","work_id":"47444c02-a383-443c-8c09-f26f96a5f36c","year":2024},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.880500Z"},"links":{"cited_paper":"/paper/2411.04635","citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:19c69965262bfc3ec37dbeba5b79671887091dd32a7e56d446ab6a47b61e2acd","observation_id":"720b08bf-12f6-43b7-826f-b30b0366d93a","resolution":{"observed_at":"2026-08-12T11:30:37.914185Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-12T11:30:37.856011Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region","version":1},"reference_index":676,"source":"pdf_text","source_observed_at":"2026-08-12T11:30:37.856011Z"},"links":{"citing_paper":"/paper/2411.18141"},"observation_digest":"sha256:d718e4754a03f6b80e0a3b6b9d16878814e0dea80ad8e6d8a8a3a8cd4bbf9ea1","observation_id":"265cf6e3-6fab-4b7e-84ca-1bc09f0d3583","resolution":{"observed_at":"2026-08-12T11:30:37.856011Z","resolver_source":null,"status":"parse_uncertain"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.18141","last_updated":"2024-11-27T08:43:07Z","latest_version":1,"primary_category":"quant-ph","snapshot_observed_at":"2026-08-16T04:26:26.097281Z","submitted_at":"2024-11-27T08:43:07Z","title":"Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":0,"metadata_mismatch":3,"parse_uncertain":1,"unresolved":5,"verified_exact":0,"verified_fuzzy":26},"total_outbound_references":35},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2411.18141."}