{"as_of":"2026-08-15T14:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a490775476afab97f3ad9212b65b77ac98df98f9ea5ce6e0e439259f49b17f72","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":"2026-08-15T06:32:42.880941+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":"2026-08-12T00:52:45.295875Z","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":"2026-08-05T22:16:15.461009Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.01752","last_updated":"2024-08-03T11:16:00Z","snapshot_observed_at":"2026-08-15T04:11:25.072640Z","submitted_at":"2024-08-03T11:16:00Z","title":"Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification","version":1},"cited_work":{"arxiv_id":"2408.01752","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.01752","snapshot_observed_at":"2026-08-05T22:16:15.461009Z","title":"Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification","venue":"cs.CV","work_id":"0ff62a77-3c19-4f4a-9d19-5052813346ee","year":2024},"citing_paper":{"arxiv_id":"2508.07306","last_updated":"2025-08-10T11:41:23Z","snapshot_observed_at":"2026-08-13T20:57:58.764747Z","submitted_at":"2025-08-10T11:41:23Z","title":"DragonFruitQualityNet: A Lightweight Convolutional Neural Network for Real-Time Dragon Fruit Quality Inspection on Mobile Devices","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T22:16:14.916387Z"},"links":{"cited_paper":"/paper/2408.01752","citing_paper":"/paper/2508.07306"},"observation_digest":"sha256:3a1e8fed2af545aa1862992a5cc537da152d8c903d81febc9785925829de88bd","observation_id":"44b096d8-7b57-4f2b-ac57-53731ea59ed6","resolution":{"observed_at":"2026-08-05T22:16:15.468189Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.01752","last_updated":"2024-08-03T11:16:00Z","snapshot_observed_at":"2026-08-15T04:11:25.072640Z","submitted_at":"2024-08-03T11:16:00Z","title":"Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.01752","snapshot_observed_at":"2026-08-12T00:52:45.295875Z","title":"arXiv preprint (2024) https://doi.org/10.48550/arXiv.2408.01752","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.09998","last_updated":"2026-08-07T13:52:38Z","snapshot_observed_at":"2026-08-14T23:09:55.330593Z","submitted_at":"2026-08-07T13:52:38Z","title":"Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-12T00:52:45.295875Z"},"links":{"cited_paper":"/paper/2408.01752","citing_paper":"/paper/2608.09998"},"observation_digest":"sha256:1baa2c723331d96b4ba5987956361c41690714027d7c668db379dcfe4befd23e","observation_id":"8694974f-c0ea-49de-9c3a-0ecd5a8f8dd0","resolution":{"observed_at":"2026-08-12T00:52:45.295875Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2408.01752/citation-record","integrity":"/paper/2408.01752/integrity","json":"/paper/2408.01752/citation-record.json","paper":"/paper/2408.01752"},"outbound":[],"paper":{"arxiv_id":"2408.01752","last_updated":"2024-08-03T11:16:00Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-15T04:11:25.072640Z","submitted_at":"2024-08-03T11:16:00Z","title":"Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.01752."}