{"as_of":"2026-08-17T22:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b81e9ef8db72538075888bfaf92997916129977b29826a1660689225c0d230c5","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T20:27:28.749915Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-01T10:35:41.853461Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2001.09636","last_updated":"2020-01-27T09:14:11Z","snapshot_observed_at":"2026-08-17T14:50:54.509553Z","submitted_at":"2020-01-27T09:14:11Z","title":"Performance Analysis and Comparison of Machine and Deep Learning Algorithms for IoT Data Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.09636","snapshot_observed_at":"2026-08-04T20:27:28.749915Z","title":"Performance analysis and comparison of machine and deep learning algorithms for iot data classification,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2509.08586","last_updated":"2025-09-10T13:33:09Z","snapshot_observed_at":"2026-08-15T06:42:49.939528Z","submitted_at":"2025-09-10T13:33:09Z","title":"CNN-ViT Hybrid for Pneumonia Detection: Theory and Empiric on Limited Data without Pretraining","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T20:27:28.749915Z"},"links":{"cited_paper":"/paper/2001.09636","citing_paper":"/paper/2509.08586"},"observation_digest":"sha256:c52bdf3cacea515f36643550e96f9e7eb2b89432f68876baa5eef599e461c1a1","observation_id":"f2ea72e4-9b78-4f31-a718-3cd09233f6a2","resolution":{"observed_at":"2026-08-04T20:27:28.749915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.09636","last_updated":"2020-01-27T09:14:11Z","snapshot_observed_at":"2026-08-17T14:50:54.509553Z","submitted_at":"2020-01-27T09:14:11Z","title":"Performance Analysis and Comparison of Machine and Deep Learning Algorithms for IoT Data Classification","version":1},"cited_work":{"arxiv_id":"2001.09636","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2001.09636","snapshot_observed_at":"2026-07-01T10:35:41.853461Z","title":"Performance anal- ysis and comparison of machine and deep learning algorithms for iot data classification.ArXiv, abs/2001.09636, 2020","venue":null,"work_id":"d8264c02-1582-49f5-90b9-099cedd93bc4","year":2001},"citing_paper":{"arxiv_id":"2606.31594","last_updated":"2026-06-30T12:43:25Z","snapshot_observed_at":"2026-08-05T05:57:30.601274Z","submitted_at":"2026-06-30T12:43:25Z","title":"Comparative Analysis of Machine Learning based Intrusion Detection in Realistic IoT Networks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-01T05:23:43.258718Z"},"links":{"cited_paper":"/paper/2001.09636","citing_paper":"/paper/2606.31594"},"observation_digest":"sha256:0396a4c750f9a2a8fb41ef57714b22763bbf406ab799feb4e00f080d3285bc90","observation_id":"94b4f9c6-26e5-42d8-8ee3-97508debc9ad","resolution":{"observed_at":"2026-07-01T10:35:41.856174Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2001.09636/citation-record","integrity":"/paper/2001.09636/integrity","json":"/paper/2001.09636/citation-record.json","paper":"/paper/2001.09636"},"outbound":[],"paper":{"arxiv_id":"2001.09636","last_updated":"2020-01-27T09:14:11Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-17T14:50:54.509553Z","submitted_at":"2020-01-27T09:14:11Z","title":"Performance Analysis and Comparison of Machine and Deep Learning Algorithms for IoT Data Classification"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2001.09636."}