{"as_of":"2026-08-21T04:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7c4f91a7afb3608768b817d5d1c7c8d1c19f1be0dbba7018667e8cf719c5aa6b","coverage":[{"denominator":10,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-28T04:04:49.690338Z","state":"measured"},{"denominator":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2606.04838/citation-record","integrity":"/paper/2606.04838/integrity","json":"/paper/2606.04838/citation-record.json","paper":"/paper/2606.04838"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T04:04:49.690338Z","title":"Key Performance Indicators (KPI) for Evolved Universal Terrestrial Radio Access Network (E-UTRAN)","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:75e7ef544d97bc0f306d2ef036fb20061f69b820274706b7298b7156f2c40343","observation_id":"c20cc3dc-3b57-4b10-b3d7-8e445c3adc7d","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","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":"2026-06-28T04:04:49.690338Z","title":"Radio measurement collection for Minimization of Drive Tests (MDT); Overall description; Stage 2","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:dba43bda015f8261c81dfdd1b39d96af70ad936ca0eee56ae26ae32af3fee58e","observation_id":"deb0a088-15c4-4997-9745-82a511401206","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","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":"2026-06-28T04:04:49.690338Z","title":"Autonomous Network Levels Evaluation Methodology","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:cebf41747d5d00a65cc898c60e5af8f918dfe71e5935c38e971805155e14cf2a","observation_id":"6cb53982-a74b-40bf-81d4-570a361fbf4d","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","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":"2026-06-28T04:04:49.690338Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:296088a7a9b227817d602d31aaf0b39916a08faf99c8044b300c4f7f0d272bc7","observation_id":"eeaef88a-d752-4107-bce6-88e6cd799069","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","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":"2026-06-28T04:04:49.690338Z","title":", year = 1951, month=aug, Address =","venue":null,"work_id":null,"year":1951},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:844ff3d3b73950f58c4792da440f79f4b7d6adb44a0a25afde5f361a3a6a3927","observation_id":"4eaac452-1aae-4129-9216-f28691a47211","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","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":"2026-06-28T04:04:49.690338Z","title":"Minimizing age of information in vehicular networks , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:107b0b47085c296d5370a2269ad1b78545e367dec4246c5f2ccb8a03136a766c","observation_id":"e84e63f7-8019-4bf5-a290-8d6a9e96f28a","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.02754","last_updated":"2016-06-10T23:23:51Z","snapshot_observed_at":"2026-08-14T22:06:53.808328Z","submitted_at":"2016-03-09T01:11:51Z","title":"XGBoost: A Scalable Tree Boosting System","version":3},"cited_work":{"arxiv_id":"1603.02754","doi":"10.48550/arxiv.1603.02754","metadata_source":"pith","pith_arxiv_id":"1603.02754","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"XGBoost: A Scalable Tree Boosting System","venue":"cs.LG","work_id":"1b87323d-bb68-4e84-943e-d0e080e5c3ad","year":2016},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"cited_paper":"/paper/1603.02754","citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:27ddf8870e6920e9eef55e68e04b4b8b90411b3263944ebc4adea3d0e8af28e0","observation_id":"aa7c4bb3-3209-4550-9424-546ac95663b8","resolution":{"observed_at":"2026-07-02T11:26:54.084101Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-14T22:38:12.742215+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-14T22:38:12.742215+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-06-28T04:04:49.690338Z","title":"and Alammouri, Ahmad and Alkhateeb, Ahmed and Andrews, Jeffrey G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:335bb3eb793cc29693cf3a3377708ab3e76327df94c558892477571d99570c0e","observation_id":"ef52bd87-5c4b-43f2-a212-6d6d170f0f3f","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","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":"2026-06-28T04:04:49.690338Z","title":"and Hoydis, Jakob , journal=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:ece8a7c998d91e8b0702c47b0e44cb3000cb8b0eddd4f1dd26f4d78814480b42","observation_id":"d5e928fb-381f-4e4b-a4f6-5fbaa256c6e5","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","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":"2026-06-28T04:04:49.690338Z","title":"2016 , Address =","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-06-28T04:04:49.690338Z"},"links":{"citing_paper":"/paper/2606.04838"},"observation_digest":"sha256:afb8d81ef0e8d4b6ddcd3beabf18329a030df4905aa3e4f71a372c0680846cfb","observation_id":"41bc0c68-67aa-488a-8825-30446910cfe4","resolution":{"observed_at":"2026-06-28T04:04:49.690338Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.04838","last_updated":"2026-06-03T13:08:29Z","latest_version":1,"primary_category":"cs.NI","snapshot_observed_at":"2026-08-12T12:59:30.308044Z","submitted_at":"2026-06-03T13:08:29Z","title":"From Network Experience to Subscriber Retention: An Explainable AI Framework for Mobile Operators"},"reference_resolution":{"displayed":10,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":10},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2606.04838."}