{"as_of":"2026-08-09T09:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7f462bcefc1fad0a7363cd2655bfdfcc3b834108d481054f04b44a10d07d6cd9","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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":"2026-05-16T10:56:30.810795Z","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":"2026-05-16T10:57:46.376332Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2012.08405","last_updated":"2022-09-11T15:46:56Z","snapshot_observed_at":"2026-08-07T21:04:33.257767Z","submitted_at":"2020-12-15T16:29:49Z","title":"Model-Based Deep Learning","version":3},"cited_work":{"arxiv_id":"2012.08405","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2012.08405","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2012.08405","venue":null,"work_id":"f26fa271-8ee8-4238-98de-873b4787b6dd","year":2012},"citing_paper":{"arxiv_id":"2601.18399","last_updated":"2026-04-27T11:08:23Z","snapshot_observed_at":"2026-08-02T12:54:06.677757Z","submitted_at":"2026-01-26T11:57:28Z","title":"Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-16T10:56:30.810795Z"},"links":{"cited_paper":"/paper/2012.08405","citing_paper":"/paper/2601.18399"},"observation_digest":"sha256:499b3f9770e2cb7c4436da34e8acc833706e72e514e9ee4a724307253cc57a77","observation_id":"e5687069-6941-4ed0-8c14-f69ef4b624da","resolution":{"observed_at":"2026-05-16T10:57:46.378646Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2012.08405/citation-record","integrity":"/paper/2012.08405/integrity","json":"/paper/2012.08405/citation-record.json","paper":"/paper/2012.08405"},"outbound":[],"paper":{"arxiv_id":"2012.08405","last_updated":"2022-09-11T15:46:56Z","latest_version":3,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-07T21:04:33.257767Z","submitted_at":"2020-12-15T16:29:49Z","title":"Model-Based Deep Learning"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2012.08405."}