{"as_of":"2026-08-15T06:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2d52041d6839878b7768e4c4273f0c929d9d75a530dda8b81a865b2e307dbd18","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":"2026-08-14T06:32:32.682623+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":"2026-08-10T13:36:16.066913Z","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":"2026-08-10T13:36:17.100342Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2102.10271","last_updated":"2022-10-11T19:49:51Z","snapshot_observed_at":"2026-08-14T18:49:34.754751Z","submitted_at":"2021-02-20T06:41:08Z","title":"Meta-Learning Dynamics Forecasting Using Task Inference","version":5},"cited_work":{"arxiv_id":"2102.10271","doi":null,"metadata_source":"pith","pith_arxiv_id":"2102.10271","snapshot_observed_at":"2026-08-10T13:36:17.100342Z","title":"Meta-Learning Dynamics Forecasting Using Task Inference","venue":"cs.LG","work_id":"ca1e1c4b-cb83-4209-94a3-1aa176e79de5","year":2021},"citing_paper":{"arxiv_id":"2501.16325","last_updated":"2025-07-31T06:57:11Z","snapshot_observed_at":"2026-08-14T17:58:13.844748Z","submitted_at":"2025-01-27T18:58:04Z","title":"Tailored Forecasting from Short Time Series via Meta-learning","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T13:36:16.066913Z"},"links":{"cited_paper":"/paper/2102.10271","citing_paper":"/paper/2501.16325"},"observation_digest":"sha256:d33a64c7b2d3d31838f7a63ed1214afdbc7a68f42e1f2d1fbd83df1fc4281d01","observation_id":"451fce9b-e304-4f72-a63c-36a169226432","resolution":{"observed_at":"2026-08-10T13:36:17.105849Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2102.10271/citation-record","integrity":"/paper/2102.10271/integrity","json":"/paper/2102.10271/citation-record.json","paper":"/paper/2102.10271"},"outbound":[],"paper":{"arxiv_id":"2102.10271","last_updated":"2022-10-11T19:49:51Z","latest_version":5,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T18:49:34.754751Z","submitted_at":"2021-02-20T06:41:08Z","title":"Meta-Learning Dynamics Forecasting Using Task Inference"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2102.10271."}