{"as_of":"2026-08-17T09:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a6734ff8347c0c6b451d533683ffcb3ce4fcb07d769915d71919054ccd7c5f11","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":"2026-08-14T14:26:01.346633Z","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":"2026-05-11T10:01:01.707148Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1610.01439","last_updated":"2016-10-05T14:26:27Z","snapshot_observed_at":"2026-08-14T21:36:36.583188Z","submitted_at":"2016-10-05T14:26:27Z","title":"Nonlinear Systems Identification Using Deep Dynamic Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.01439","snapshot_observed_at":"2026-08-14T14:26:01.346633Z","title":"Nonlinear Systems Identiﬁcation Using Deep Dynamic Neural Networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.03269","last_updated":"2019-08-08T21:26:41Z","snapshot_observed_at":"2026-08-15T22:45:21.027162Z","submitted_at":"2019-08-08T21:26:41Z","title":"Neural-Learning Trajectory Tracking Control of Flexible-Joint Robot Manipulators with Unknown Dynamics","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T14:26:01.346633Z"},"links":{"cited_paper":"/paper/1610.01439","citing_paper":"/paper/1908.03269"},"observation_digest":"sha256:1a9ab98883e66d271f0bc0fc663291f621b1b46279fb25c1a245aa97a660b46b","observation_id":"8f5e0b0c-d3c0-46d7-89a8-50e8a063122e","resolution":{"observed_at":"2026-08-14T14:26:01.346633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1610.01439","last_updated":"2016-10-05T14:26:27Z","snapshot_observed_at":"2026-08-14T21:36:36.583188Z","submitted_at":"2016-10-05T14:26:27Z","title":"Nonlinear Systems Identification Using Deep Dynamic Neural Networks","version":1},"cited_work":{"arxiv_id":"1610.01439","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1610.01439","snapshot_observed_at":"2026-07-04T21:27:19.891292Z","title":"Nonlinear systems identifica- tion using deep dynamic neural networks","venue":null,"work_id":"9a349e2d-ae8b-455f-ac4e-7495a07b2840","year":2016},"citing_paper":{"arxiv_id":"2605.01914","last_updated":"2026-05-03T14:51:20Z","snapshot_observed_at":"2026-08-13T00:18:00.186113Z","submitted_at":"2026-05-03T14:51:20Z","title":"Deep learning-based pavement performance modeling using multiple distress indicators and road work history","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-10T15:41:59.201544Z"},"links":{"cited_paper":"/paper/1610.01439","citing_paper":"/paper/2605.01914"},"observation_digest":"sha256:ea234e06f10a121f29e0b0b9db0991d629295594af109d673399011424a432c8","observation_id":"edaf7e9f-4ae9-44ce-87a9-735d78420cce","resolution":{"observed_at":"2026-07-04T21:27:19.891292Z","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/1610.01439/citation-record","integrity":"/paper/1610.01439/integrity","json":"/paper/1610.01439/citation-record.json","paper":"/paper/1610.01439"},"outbound":[],"paper":{"arxiv_id":"1610.01439","last_updated":"2016-10-05T14:26:27Z","latest_version":1,"primary_category":"cs.NE","snapshot_observed_at":"2026-08-14T21:36:36.583188Z","submitted_at":"2016-10-05T14:26:27Z","title":"Nonlinear Systems Identification Using Deep Dynamic Neural Networks"},"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:1610.01439."}