{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:FDKEROFN6KKXHGDE2Q6OHRPPSX","short_pith_number":"pith:FDKEROFN","schema_version":"1.0","canonical_sha256":"28d448b8adf295739864d43ce3c5ef95edcad89d24180792ff7a33681a00b538","source":{"kind":"arxiv","id":"2307.07930","version":1},"attestation_state":"computed","paper":{"title":"GeoGPT: Understanding and Processing Geospatial Tasks through An Autonomous GPT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cheng Wei, Shangyou Wu, Wenhao Yu, Yifan Zhang, Zhengting He","submitted_at":"2023-07-16T03:03:59Z","abstract_excerpt":"Decision-makers in GIS need to combine a series of spatial algorithms and operations to solve geospatial tasks. For example, in the task of facility siting, the Buffer tool is usually first used to locate areas close or away from some specific entities; then, the Intersect or Erase tool is used to select candidate areas satisfied multiple requirements. Though professionals can easily understand and solve these geospatial tasks by sequentially utilizing relevant tools, it is difficult for non-professionals to handle these problems. Recently, Generative Pre-trained Transformer (e.g., ChatGPT) pr"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2307.07930","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-07-16T03:03:59Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c87984dff6af94d3143d334463cedb465f74bb6d8ad19b0557b0840e2bb8abbd","abstract_canon_sha256":"f9322d025b138bfe7c6a530c513649d91b7e43efcfdaaad8c59a1b80152c93c9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:31:17.835006Z","signature_b64":"H8TXGDJd2OHFoixiDVfFMRfwLqh06wXg9fE+ImkIQGO+Erfi+SD0ge2vlWRoTAWQTMpPkalcOutrUG40u2eXBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"28d448b8adf295739864d43ce3c5ef95edcad89d24180792ff7a33681a00b538","last_reissued_at":"2026-07-05T06:31:17.834453Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:31:17.834453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GeoGPT: Understanding and Processing Geospatial Tasks through An Autonomous GPT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cheng Wei, Shangyou Wu, Wenhao Yu, Yifan Zhang, Zhengting He","submitted_at":"2023-07-16T03:03:59Z","abstract_excerpt":"Decision-makers in GIS need to combine a series of spatial algorithms and operations to solve geospatial tasks. For example, in the task of facility siting, the Buffer tool is usually first used to locate areas close or away from some specific entities; then, the Intersect or Erase tool is used to select candidate areas satisfied multiple requirements. Though professionals can easily understand and solve these geospatial tasks by sequentially utilizing relevant tools, it is difficult for non-professionals to handle these problems. Recently, Generative Pre-trained Transformer (e.g., ChatGPT) pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.07930","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/2307.07930/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2307.07930","created_at":"2026-07-05T06:31:17.834522+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.07930v1","created_at":"2026-07-05T06:31:17.834522+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.07930","created_at":"2026-07-05T06:31:17.834522+00:00"},{"alias_kind":"pith_short_12","alias_value":"FDKEROFN6KKX","created_at":"2026-07-05T06:31:17.834522+00:00"},{"alias_kind":"pith_short_16","alias_value":"FDKEROFN6KKXHGDE","created_at":"2026-07-05T06:31:17.834522+00:00"},{"alias_kind":"pith_short_8","alias_value":"FDKEROFN","created_at":"2026-07-05T06:31:17.834522+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2407.01846","citing_title":"Investigating the Segment Anything Foundation Model for Mapping Smallholder Agriculture Field Boundaries Without Training Labels","ref_index":17,"is_internal_anchor":false},{"citing_arxiv_id":"2605.22811","citing_title":"GS-QA: A Benchmark for Geospatial Question Answering","ref_index":66,"is_internal_anchor":false},{"citing_arxiv_id":"2511.00739","citing_title":"Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective","ref_index":42,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX","json":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX.json","graph_json":"https://pith.science/api/pith-number/FDKEROFN6KKXHGDE2Q6OHRPPSX/graph.json","events_json":"https://pith.science/api/pith-number/FDKEROFN6KKXHGDE2Q6OHRPPSX/events.json","paper":"https://pith.science/paper/FDKEROFN"},"agent_actions":{"view_html":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX","download_json":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX.json","view_paper":"https://pith.science/paper/FDKEROFN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.07930&json=true","fetch_graph":"https://pith.science/api/pith-number/FDKEROFN6KKXHGDE2Q6OHRPPSX/graph.json","fetch_events":"https://pith.science/api/pith-number/FDKEROFN6KKXHGDE2Q6OHRPPSX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX/action/storage_attestation","attest_author":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX/action/author_attestation","sign_citation":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX/action/citation_signature","submit_replication":"https://pith.science/pith/FDKEROFN6KKXHGDE2Q6OHRPPSX/action/replication_record"}},"created_at":"2026-07-05T06:31:17.834522+00:00","updated_at":"2026-07-05T06:31:17.834522+00:00"}