{"as_of":"2026-08-09T16:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ab3cf3000a1657cb8002ebcd99bfb8e0c9210735ff9ffd59b64bb9bb45bcae4e","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":"2026-08-04T12:48:32.685898Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2503.14473","last_updated":"2025-03-18T17:48:03Z","snapshot_observed_at":"2026-08-08T18:41:04.359846Z","submitted_at":"2025-03-18T17:48:03Z","title":"EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.14473","snapshot_observed_at":"2026-08-04T12:48:32.685898Z","title":"Enqode: Fast amplitude embedding for quantum machine learning using classical data.arXiv preprint arXiv:2503.14473,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.02497","last_updated":"2026-05-25T17:40:10Z","snapshot_observed_at":"2026-08-09T14:00:02.087752Z","submitted_at":"2025-10-02T19:00:41Z","title":"HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T12:48:32.685898Z"},"links":{"cited_paper":"/paper/2503.14473","citing_paper":"/paper/2510.02497"},"observation_digest":"sha256:8aa48bf029d9fddbe5634e0f439883469f66b612f09ab8dd005cd176b99d45eb","observation_id":"6cacc3b7-ea28-4d01-b413-2fd849c39d78","resolution":{"observed_at":"2026-08-04T12:48:32.685898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2503.14473/citation-record","integrity":"/paper/2503.14473/integrity","json":"/paper/2503.14473/citation-record.json","paper":"/paper/2503.14473"},"outbound":[],"paper":{"arxiv_id":"2503.14473","last_updated":"2025-03-18T17:48:03Z","latest_version":1,"primary_category":"quant-ph","snapshot_observed_at":"2026-08-08T18:41:04.359846Z","submitted_at":"2025-03-18T17:48:03Z","title":"EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data"},"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:2503.14473."}