{"as_of":"2026-08-09T05:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9d5377e0b8a53c00a03c182af186db70b033f653255a7d03e0553c33ba964009","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":"2026-08-08T06:32:00.761636+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":"2026-08-06T21:07:16.885754Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T06:16:28.064256Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1712.04443","last_updated":"2017-12-12T05:28:12Z","snapshot_observed_at":"2026-07-06T06:14:02.995462Z","submitted_at":"2017-12-12T05:28:12Z","title":"Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks","version":1},"cited_work":{"arxiv_id":"1712.04443","doi":"10.48550/arxiv.1712.04443","metadata_source":"pith","pith_arxiv_id":"1712.04443","snapshot_observed_at":"2026-08-07T06:16:28.064256Z","title":"Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks","venue":"cs.SI","work_id":"215e04dd-63c8-496d-aa64-46b408d2db7a","year":2017},"citing_paper":{"arxiv_id":"2507.00926","last_updated":"2025-07-01T16:31:50Z","snapshot_observed_at":"2026-08-08T08:55:42.621712Z","submitted_at":"2025-07-01T16:31:50Z","title":"HyperFusion: Hierarchical Multimodal Ensemble Learning for Social Media Popularity Prediction","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T21:07:16.885754Z"},"links":{"cited_paper":"/paper/1712.04443","citing_paper":"/paper/2507.00926"},"observation_digest":"sha256:abe939f83a399404754d44f06b9b3e1c267de9793fa4e5486387691ca89ead13","observation_id":"4185541d-06d5-477d-8f77-05f83e50e1f5","resolution":{"observed_at":"2026-08-06T21:07:16.960788Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1712.04443","last_updated":"2017-12-12T05:28:12Z","snapshot_observed_at":"2026-07-06T06:14:02.995462Z","submitted_at":"2017-12-12T05:28:12Z","title":"Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.04443","snapshot_observed_at":"2026-08-01T13:11:38.084752Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.19200","last_updated":"2026-07-21T15:34:11Z","snapshot_observed_at":"2026-08-04T14:43:27.972036Z","submitted_at":"2026-07-21T15:34:11Z","title":"Enhancing Relation Modeling with Social Attributes for Social Media Popularity Prediction","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-01T13:11:38.084752Z"},"links":{"cited_paper":"/paper/1712.04443","citing_paper":"/paper/2607.19200"},"observation_digest":"sha256:8379f5ad19811bed89af8cfbac75d4f12e7156d0e1970dbfe66ed4bf4c71d571","observation_id":"2e33f13c-c049-49d8-83d8-728362f616f1","resolution":{"observed_at":"2026-08-01T13:11:38.084752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1712.04443/citation-record","integrity":"/paper/1712.04443/integrity","json":"/paper/1712.04443/citation-record.json","paper":"/paper/1712.04443"},"outbound":[],"paper":{"arxiv_id":"1712.04443","last_updated":"2017-12-12T05:28:12Z","latest_version":1,"primary_category":"cs.SI","snapshot_observed_at":"2026-07-06T06:14:02.995462Z","submitted_at":"2017-12-12T05:28:12Z","title":"Sequential Prediction of Social Media Popularity with Deep Temporal Context 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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1712.04443."}