{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:72T33NN2RFG4U2MFMJY7UCF5MX","short_pith_number":"pith:72T33NN2","canonical_record":{"source":{"id":"2103.14587","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-25T13:47:56Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"0f506a06aaf7441e161bffa62988f392f7c812bc37feca9bcbc6f5107e76bdca","abstract_canon_sha256":"3938a28fcf0e69164e84382da593fd85cfe57426e4bcc44ab1098df5175dfffd"},"schema_version":"1.0"},"canonical_sha256":"fea7bdb5ba894dca69856271fa08bd65f3197e1c125ce787fe1d2e61a6fbe4de","source":{"kind":"arxiv","id":"2103.14587","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.14587","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"arxiv_version","alias_value":"2103.14587v1","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.14587","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"pith_short_12","alias_value":"72T33NN2RFG4","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"pith_short_16","alias_value":"72T33NN2RFG4U2MF","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"pith_short_8","alias_value":"72T33NN2","created_at":"2026-07-05T02:26:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:72T33NN2RFG4U2MFMJY7UCF5MX","target":"record","payload":{"canonical_record":{"source":{"id":"2103.14587","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-25T13:47:56Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"0f506a06aaf7441e161bffa62988f392f7c812bc37feca9bcbc6f5107e76bdca","abstract_canon_sha256":"3938a28fcf0e69164e84382da593fd85cfe57426e4bcc44ab1098df5175dfffd"},"schema_version":"1.0"},"canonical_sha256":"fea7bdb5ba894dca69856271fa08bd65f3197e1c125ce787fe1d2e61a6fbe4de","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:26:42.652236Z","signature_b64":"UXv5q8rlQFRKpIRDGSwtfD8Nc4pepg8xgl+I7VcSyb8qYoXdjakZTN8uAAB1irRXEbR34+8jdYHD2nKpGAhHCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fea7bdb5ba894dca69856271fa08bd65f3197e1c125ce787fe1d2e61a6fbe4de","last_reissued_at":"2026-07-05T02:26:42.651874Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:26:42.651874Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.14587","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:26:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uiyOASXdnNbtcIF2pZ2n15x9/UboPR+cQhYLSUi/RD60vDa7SNY2UwUJmRsW+w7fob1vDxU0tsn2q80+HUoBDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:25:34.231994Z"},"content_sha256":"ab7581206393e5504477f24314d3dd4bdf32da0c785a2149783ed21aa5b828f0","schema_version":"1.0","event_id":"sha256:ab7581206393e5504477f24314d3dd4bdf32da0c785a2149783ed21aa5b828f0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:72T33NN2RFG4U2MFMJY7UCF5MX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep-AIR: A Hybrid CNN-LSTM Framework for Air Quality Modeling in Metropolitan Cities","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.LG","authors_text":"Jacqueline C.K. Lam, Qi Zhang, Victor O.K. Li, Yang Han","submitted_at":"2021-03-25T13:47:56Z","abstract_excerpt":"Air pollution has long been a serious environmental health challenge, especially in metropolitan cities, where air pollutant concentrations are exacerbated by the street canyon effect and high building density. Whilst accurately monitoring and forecasting air pollution are highly crucial, existing data-driven models fail to fully address the complex interaction between air pollution and urban dynamics. Our Deep-AIR, a novel hybrid deep learning framework that combines a convolutional neural network with a long short-term memory network, aims to address this gap to provide fine-grained city-wid"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.14587","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2103.14587/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:26:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h9ERq+hvyJq+eG1GQgG71wMZp9+CaYk1aoECaiI6/H5YcxWduGzpMUgTQwTJ7JQZWGaJxS06viQx5FJZndozDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:25:34.232506Z"},"content_sha256":"00b3f54283b9f71c4b2e79d34e7c3d28d393ec57243c6d7866565971f8141ed3","schema_version":"1.0","event_id":"sha256:00b3f54283b9f71c4b2e79d34e7c3d28d393ec57243c6d7866565971f8141ed3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/72T33NN2RFG4U2MFMJY7UCF5MX/bundle.json","state_url":"https://pith.science/pith/72T33NN2RFG4U2MFMJY7UCF5MX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/72T33NN2RFG4U2MFMJY7UCF5MX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-06T13:25:34Z","links":{"resolver":"https://pith.science/pith/72T33NN2RFG4U2MFMJY7UCF5MX","bundle":"https://pith.science/pith/72T33NN2RFG4U2MFMJY7UCF5MX/bundle.json","state":"https://pith.science/pith/72T33NN2RFG4U2MFMJY7UCF5MX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/72T33NN2RFG4U2MFMJY7UCF5MX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:72T33NN2RFG4U2MFMJY7UCF5MX","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":"3938a28fcf0e69164e84382da593fd85cfe57426e4bcc44ab1098df5175dfffd","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-25T13:47:56Z","title_canon_sha256":"0f506a06aaf7441e161bffa62988f392f7c812bc37feca9bcbc6f5107e76bdca"},"schema_version":"1.0","source":{"id":"2103.14587","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.14587","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"arxiv_version","alias_value":"2103.14587v1","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.14587","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"pith_short_12","alias_value":"72T33NN2RFG4","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"pith_short_16","alias_value":"72T33NN2RFG4U2MF","created_at":"2026-07-05T02:26:42Z"},{"alias_kind":"pith_short_8","alias_value":"72T33NN2","created_at":"2026-07-05T02:26:42Z"}],"graph_snapshots":[{"event_id":"sha256:00b3f54283b9f71c4b2e79d34e7c3d28d393ec57243c6d7866565971f8141ed3","target":"graph","created_at":"2026-07-05T02:26:42Z","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/2103.14587/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Air pollution has long been a serious environmental health challenge, especially in metropolitan cities, where air pollutant concentrations are exacerbated by the street canyon effect and high building density. Whilst accurately monitoring and forecasting air pollution are highly crucial, existing data-driven models fail to fully address the complex interaction between air pollution and urban dynamics. Our Deep-AIR, a novel hybrid deep learning framework that combines a convolutional neural network with a long short-term memory network, aims to address this gap to provide fine-grained city-wid","authors_text":"Jacqueline C.K. Lam, Qi Zhang, Victor O.K. Li, Yang Han","cross_cats":["cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-25T13:47:56Z","title":"Deep-AIR: A Hybrid CNN-LSTM Framework for Air Quality Modeling in Metropolitan Cities"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.14587","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:ab7581206393e5504477f24314d3dd4bdf32da0c785a2149783ed21aa5b828f0","target":"record","created_at":"2026-07-05T02:26:42Z","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":"3938a28fcf0e69164e84382da593fd85cfe57426e4bcc44ab1098df5175dfffd","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-25T13:47:56Z","title_canon_sha256":"0f506a06aaf7441e161bffa62988f392f7c812bc37feca9bcbc6f5107e76bdca"},"schema_version":"1.0","source":{"id":"2103.14587","kind":"arxiv","version":1}},"canonical_sha256":"fea7bdb5ba894dca69856271fa08bd65f3197e1c125ce787fe1d2e61a6fbe4de","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fea7bdb5ba894dca69856271fa08bd65f3197e1c125ce787fe1d2e61a6fbe4de","first_computed_at":"2026-07-05T02:26:42.651874Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:26:42.651874Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UXv5q8rlQFRKpIRDGSwtfD8Nc4pepg8xgl+I7VcSyb8qYoXdjakZTN8uAAB1irRXEbR34+8jdYHD2nKpGAhHCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:26:42.652236Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.14587","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab7581206393e5504477f24314d3dd4bdf32da0c785a2149783ed21aa5b828f0","sha256:00b3f54283b9f71c4b2e79d34e7c3d28d393ec57243c6d7866565971f8141ed3"],"state_sha256":"70a9099ee3f87dd9780f7e9da59552dab5a9d16dd3fc7d87f9d1aab09a8d39c3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ze+967xDF5jT6Ld/B1hwIOIMHAHvy3zDlytKPQJSWPD7UwwI/oKXV7UkZ+fLEQtrCEcX5djurKfmFg/339FVAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T13:25:34.237058Z","bundle_sha256":"0f15a1f32950c28bd04502823cd9b637e7818ed02d93d141e26c46423ec68ffc"}}