{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LEHCP4BMLLG2RNB6PVZAXJR373","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"66897123dec08abfc4fd50575367628a1f4d5d19f8e7bd5cfbc1949f575cb2b1","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-09T23:56:35Z","title_canon_sha256":"feacbc9033730fe045afd513dd918cf9a5ecc05114343333d4377c1e1dcf4e44"},"schema_version":"1.0","source":{"id":"2211.05267","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.05267","created_at":"2026-07-05T05:15:02Z"},{"alias_kind":"arxiv_version","alias_value":"2211.05267v1","created_at":"2026-07-05T05:15:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.05267","created_at":"2026-07-05T05:15:02Z"},{"alias_kind":"pith_short_12","alias_value":"LEHCP4BMLLG2","created_at":"2026-07-05T05:15:02Z"},{"alias_kind":"pith_short_16","alias_value":"LEHCP4BMLLG2RNB6","created_at":"2026-07-05T05:15:02Z"},{"alias_kind":"pith_short_8","alias_value":"LEHCP4BM","created_at":"2026-07-05T05:15:02Z"}],"graph_snapshots":[{"event_id":"sha256:b6a772c1f374651abbbe8d7a0e50456ab41f467acb59ed99978f542c9946fe51","target":"graph","created_at":"2026-07-05T05:15:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2211.05267/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecasting and monitoring research using artificial neural networks (ANNs). Most of the prior work relied on modeling pollutant concentrations collected from ground-based monitors and meteorological data for long-term forecasting of outdoor ozone, oxides of nitrogen, and PM2.5. Given that traditional, highly sophisticated air quality monitors are expensive and are not universally available, these models cannot adequately s","authors_text":"Chen Lin, Donghai Liang, Elvis Kahoro, Eugene Agichtein, Jeremy Sarnat, Payam Karisani, Safoora Yousefi","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-09T23:56:35Z","title":"Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.05267","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7920c6af70a9b10c879f1b9f222dcb4ca4d79cc14bdc6a2dfa2869d65cf1e982","target":"record","created_at":"2026-07-05T05:15:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"66897123dec08abfc4fd50575367628a1f4d5d19f8e7bd5cfbc1949f575cb2b1","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-09T23:56:35Z","title_canon_sha256":"feacbc9033730fe045afd513dd918cf9a5ecc05114343333d4377c1e1dcf4e44"},"schema_version":"1.0","source":{"id":"2211.05267","kind":"arxiv","version":1}},"canonical_sha256":"590e27f02c5acda8b43e7d720ba63bfec61c72644594bfebf8fda40fb5aa0af8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"590e27f02c5acda8b43e7d720ba63bfec61c72644594bfebf8fda40fb5aa0af8","first_computed_at":"2026-07-05T05:15:02.635189Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:15:02.635189Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BuXXWSqKIqw8Uz7LNjo4BCX/RB4os5cloHzAixTmERpxN1hntixLnle29dz84X63TjWYHFmwsTivLD15MCv5Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T05:15:02.635665Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.05267","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7920c6af70a9b10c879f1b9f222dcb4ca4d79cc14bdc6a2dfa2869d65cf1e982","sha256:b6a772c1f374651abbbe8d7a0e50456ab41f467acb59ed99978f542c9946fe51"],"state_sha256":"bd5e4ebbff186d9dd7d7cadb06b45e76af2520f957f98d9933a0b0bfa7f6bf01"}