{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:RMW5R6IR3NEIOVG3YMDUSH7QOM","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":"cbcd5013ee2c78ee8a5b302bff6123b7eb7d23a0831d5ade3fe543621f234d95","cross_cats_sorted":["cs.AI","econ.GN","q-fin.EC"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-03T21:45:36Z","title_canon_sha256":"b2fc50ae08c5d6d33e27e5c9202fd60e20d113e0790d1fe3af24165b1c653ac3"},"schema_version":"1.0","source":{"id":"2303.02230","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.02230","created_at":"2026-07-05T06:18:20Z"},{"alias_kind":"arxiv_version","alias_value":"2303.02230v2","created_at":"2026-07-05T06:18:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.02230","created_at":"2026-07-05T06:18:20Z"},{"alias_kind":"pith_short_12","alias_value":"RMW5R6IR3NEI","created_at":"2026-07-05T06:18:20Z"},{"alias_kind":"pith_short_16","alias_value":"RMW5R6IR3NEIOVG3","created_at":"2026-07-05T06:18:20Z"},{"alias_kind":"pith_short_8","alias_value":"RMW5R6IR","created_at":"2026-07-05T06:18:20Z"}],"graph_snapshots":[{"event_id":"sha256:8130b9192428e432de0065f0c21edfab5d97c855ca27a929ee56a49ebced28e6","target":"graph","created_at":"2026-07-05T06:18:20Z","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/2303.02230/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper provides a first milestone in measuring the floorspace of buildings (that is, building footprint and height) for 40 major Chinese cities. The intent is to maximize city coverage and, eventually provide longitudinal data. Doing so requires building on imagery that is of a medium-fine-grained granularity, as larger cross sections of cities and longer time series for them are only available in such format. We use a multi-task object segmenter approach to learn the building footprint and height in the same framework in parallel: (1) we determine the surface area is covered by any buildi","authors_text":"Peter Egger, Sebastiano Papini, Susie Xi Rao","cross_cats":["cs.AI","econ.GN","q-fin.EC"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-03T21:45:36Z","title":"Building Floorspace in China: A Dataset and Learning Pipeline"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.02230","kind":"arxiv","version":2},"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:be0083124cb93c4bbb0bb683d118864152f8c203ee4f77e6d3594ca180d49b10","target":"record","created_at":"2026-07-05T06:18:20Z","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":"cbcd5013ee2c78ee8a5b302bff6123b7eb7d23a0831d5ade3fe543621f234d95","cross_cats_sorted":["cs.AI","econ.GN","q-fin.EC"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-03T21:45:36Z","title_canon_sha256":"b2fc50ae08c5d6d33e27e5c9202fd60e20d113e0790d1fe3af24165b1c653ac3"},"schema_version":"1.0","source":{"id":"2303.02230","kind":"arxiv","version":2}},"canonical_sha256":"8b2dd8f911db488754dbc307491ff0732a7013374ae2748d98d8ac0137697745","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b2dd8f911db488754dbc307491ff0732a7013374ae2748d98d8ac0137697745","first_computed_at":"2026-07-05T06:18:20.957210Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:18:20.957210Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"imT6it55ecFjo0FbUH+Ml712u8SaCsaXRM78iYkmZvNF9UBiUeq8shyeWYZSn4CTVciXqgAzO8tyNX0h/3TQBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:18:20.957659Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.02230","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be0083124cb93c4bbb0bb683d118864152f8c203ee4f77e6d3594ca180d49b10","sha256:8130b9192428e432de0065f0c21edfab5d97c855ca27a929ee56a49ebced28e6"],"state_sha256":"a9653ce9eae1bf685ed6034cda9b0fe263e8b7365bd617b9a06d00687b9928bc"}