{"as_of":"2026-08-22T06:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1b92ee506d9e1bc03e1e207ed75d2483564615dbc5160ae2d832d107fa489139","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T18:14:35.215146Z","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":"2026-05-11T13:21:19.240873Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2301.10416","last_updated":"2023-02-12T11:58:22Z","snapshot_observed_at":"2026-08-21T21:08:58.811447Z","submitted_at":"2023-01-24T04:23:20Z","title":"AI vs. Human -- Differentiation Analysis of Scientific Content Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10416","snapshot_observed_at":"2026-08-12T18:14:35.215146Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11736","last_updated":"2024-11-18T17:03:30Z","snapshot_observed_at":"2026-08-18T11:53:42.279213Z","submitted_at":"2024-11-18T17:03:30Z","title":"Advacheck at GenAI Detection Task 1: AI Detection Powered by Domain-Aware Multi-Tasking","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-12T18:14:35.215146Z"},"links":{"cited_paper":"/paper/2301.10416","citing_paper":"/paper/2411.11736"},"observation_digest":"sha256:8f254c72514f5b85b3d2beb99dc43ce323a576c5581489b80f813b14f6267efc","observation_id":"8e1ecab0-7004-43dc-af29-3140d5f91b7c","resolution":{"observed_at":"2026-08-12T18:14:35.215146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10416","last_updated":"2023-02-12T11:58:22Z","snapshot_observed_at":"2026-08-21T21:08:58.811447Z","submitted_at":"2023-01-24T04:23:20Z","title":"AI vs. Human -- Differentiation Analysis of Scientific Content Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10416","snapshot_observed_at":"2026-08-11T22:53:42.815164Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03025","last_updated":"2024-12-04T04:38:35Z","snapshot_observed_at":"2026-08-15T12:08:43.355257Z","submitted_at":"2024-12-04T04:38:35Z","title":"Human Variability vs. Machine Consistency: A Linguistic Analysis of Texts Generated by Humans and Large Language Models","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-11T22:53:42.815164Z"},"links":{"cited_paper":"/paper/2301.10416","citing_paper":"/paper/2412.03025"},"observation_digest":"sha256:25c28881273d0f8398d4152269b897dfda6ad02bbc05ab5e5e11f28926bc9227","observation_id":"f4602bd7-c295-400f-b559-e630b7a4b51f","resolution":{"observed_at":"2026-08-11T22:53:42.815164Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10416","last_updated":"2023-02-12T11:58:22Z","snapshot_observed_at":"2026-08-21T21:08:58.811447Z","submitted_at":"2023-01-24T04:23:20Z","title":"AI vs. Human -- Differentiation Analysis of Scientific Content Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10416","snapshot_observed_at":"2026-08-10T14:07:27.886557Z","title":"In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1265–1285, Online and Punta Cana, Dominican Republic","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.15654","last_updated":"2025-05-19T18:22:33Z","snapshot_observed_at":"2026-08-20T14:33:48.457204Z","submitted_at":"2025-01-26T19:31:34Z","title":"People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T14:07:27.886557Z"},"links":{"cited_paper":"/paper/2301.10416","citing_paper":"/paper/2501.15654"},"observation_digest":"sha256:375ff23027d1207d910d49c7b73b36beba384bc09a120185cd74da100e5e4a2e","observation_id":"df765ffc-e4af-4af5-829a-3fc10d5b3b43","resolution":{"observed_at":"2026-08-10T14:07:27.886557Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10416","last_updated":"2023-02-12T11:58:22Z","snapshot_observed_at":"2026-08-21T21:08:58.811447Z","submitted_at":"2023-01-24T04:23:20Z","title":"AI vs. Human -- Differentiation Analysis of Scientific Content Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10416","snapshot_observed_at":"2026-08-04T22:33:26.987526Z","title":"Is this abstract generated by ai? a research for the gap between ai-generated scientific text and human-written scientific text,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.07287","last_updated":"2025-09-08T23:44:00Z","snapshot_observed_at":"2026-08-17T20:59:00.743309Z","submitted_at":"2025-09-08T23:44:00Z","title":"Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-04T22:33:26.987526Z"},"links":{"cited_paper":"/paper/2301.10416","citing_paper":"/paper/2509.07287"},"observation_digest":"sha256:0f738ce0417a13503ccc8b2c3393ec77361c9538e678ccc8175bb7e541b18242","observation_id":"955f9f4a-1edd-4698-9fbf-dc638abc4644","resolution":{"observed_at":"2026-08-04T22:33:26.987526Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10416","last_updated":"2023-02-12T11:58:22Z","snapshot_observed_at":"2026-08-21T21:08:58.811447Z","submitted_at":"2023-01-24T04:23:20Z","title":"AI vs. Human -- Differentiation Analysis of Scientific Content Generation","version":2},"cited_work":{"arxiv_id":"2301.10416","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.10416","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Human – Diﬀerentiation Analysis of Scientiﬁc Content Generation (20 23)","venue":null,"work_id":"ebb6ddf8-0262-4c00-a8e5-2c1bdb251f29","year":null},"citing_paper":{"arxiv_id":"2604.19578","last_updated":"2026-04-21T15:33:53Z","snapshot_observed_at":"2026-08-13T05:58:06.943506Z","submitted_at":"2026-04-21T15:33:53Z","title":"Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-10T01:50:31.124812Z"},"links":{"cited_paper":"/paper/2301.10416","citing_paper":"/paper/2604.19578"},"observation_digest":"sha256:aa30729d42099b6bc35a8c1843206e3457749c20e6594bebb2c5cb13f023a4e8","observation_id":"112b29a3-041f-40f2-a11d-c4572257bc70","resolution":{"observed_at":"2026-05-11T13:21:19.286853Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2301.10416/citation-record","integrity":"/paper/2301.10416/integrity","json":"/paper/2301.10416/citation-record.json","paper":"/paper/2301.10416"},"outbound":[],"paper":{"arxiv_id":"2301.10416","last_updated":"2023-02-12T11:58:22Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-21T21:08:58.811447Z","submitted_at":"2023-01-24T04:23:20Z","title":"AI vs. Human -- Differentiation Analysis of Scientific Content Generation"},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2301.10416."}