{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:NX33GWBOOD6PZA2RW765X5YIKO","short_pith_number":"pith:NX33GWBO","schema_version":"1.0","canonical_sha256":"6df7b3582e70fcfc8351b7fddbf70853b16bf669abf734554f0a7e080d610623","source":{"kind":"arxiv","id":"2507.05651","version":1},"attestation_state":"computed","paper":{"title":"City-Level Foreign Direct Investment Prediction with Tabular Learning on Judicial Data","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jiming Wang, Lizhe Cao, Shuang Wang, Shutong Zhu, Tianxing Wu, Yerong Wu, Yuqing Feng","submitted_at":"2025-07-08T04:10:25Z","abstract_excerpt":"To advance the United Nations Sustainable Development Goal on promoting sustained, inclusive, and sustainable economic growth, foreign direct investment (FDI) plays a crucial role in catalyzing economic expansion and fostering innovation. Precise city-level FDI prediction is quite important for local government and is commonly studied based on economic data (e.g., GDP). However, such economic data could be prone to manipulation, making predictions less reliable. To address this issue, we try to leverage large-scale judicial data which reflects judicial performance influencing local investment "},"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":"2507.05651","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-07-08T04:10:25Z","cross_cats_sorted":[],"title_canon_sha256":"5dad1ee27fe5d39e62fcdb72c42cd68609aabf29dc9fbe6700bb492ccc8a2555","abstract_canon_sha256":"662ac28433ff4eaecac6ddfd5e3d2f22648cacb52857405cc6a2c7f9722d4f69"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:33:33.921111Z","signature_b64":"GdA6kTRIWISmAc2xNRKV5xln06pT3yysW0Jk4eGBv6Hc8onyrDzHgto6pefzGP9RCiaqWF92gtMoEjE+qQ3TAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6df7b3582e70fcfc8351b7fddbf70853b16bf669abf734554f0a7e080d610623","last_reissued_at":"2026-07-05T11:33:33.920679Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:33:33.920679Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"City-Level Foreign Direct Investment Prediction with Tabular Learning on Judicial Data","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jiming Wang, Lizhe Cao, Shuang Wang, Shutong Zhu, Tianxing Wu, Yerong Wu, Yuqing Feng","submitted_at":"2025-07-08T04:10:25Z","abstract_excerpt":"To advance the United Nations Sustainable Development Goal on promoting sustained, inclusive, and sustainable economic growth, foreign direct investment (FDI) plays a crucial role in catalyzing economic expansion and fostering innovation. Precise city-level FDI prediction is quite important for local government and is commonly studied based on economic data (e.g., GDP). However, such economic data could be prone to manipulation, making predictions less reliable. To address this issue, we try to leverage large-scale judicial data which reflects judicial performance influencing local investment "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.05651","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/2507.05651/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":"2507.05651","created_at":"2026-07-05T11:33:33.920735+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.05651v1","created_at":"2026-07-05T11:33:33.920735+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.05651","created_at":"2026-07-05T11:33:33.920735+00:00"},{"alias_kind":"pith_short_12","alias_value":"NX33GWBOOD6P","created_at":"2026-07-05T11:33:33.920735+00:00"},{"alias_kind":"pith_short_16","alias_value":"NX33GWBOOD6PZA2R","created_at":"2026-07-05T11:33:33.920735+00:00"},{"alias_kind":"pith_short_8","alias_value":"NX33GWBO","created_at":"2026-07-05T11:33:33.920735+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO","json":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO.json","graph_json":"https://pith.science/api/pith-number/NX33GWBOOD6PZA2RW765X5YIKO/graph.json","events_json":"https://pith.science/api/pith-number/NX33GWBOOD6PZA2RW765X5YIKO/events.json","paper":"https://pith.science/paper/NX33GWBO"},"agent_actions":{"view_html":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO","download_json":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO.json","view_paper":"https://pith.science/paper/NX33GWBO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.05651&json=true","fetch_graph":"https://pith.science/api/pith-number/NX33GWBOOD6PZA2RW765X5YIKO/graph.json","fetch_events":"https://pith.science/api/pith-number/NX33GWBOOD6PZA2RW765X5YIKO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO/action/storage_attestation","attest_author":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO/action/author_attestation","sign_citation":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO/action/citation_signature","submit_replication":"https://pith.science/pith/NX33GWBOOD6PZA2RW765X5YIKO/action/replication_record"}},"created_at":"2026-07-05T11:33:33.920735+00:00","updated_at":"2026-07-05T11:33:33.920735+00:00"}