{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XWRG6NEBL6QUQABRRUMU3ZZZAK","short_pith_number":"pith:XWRG6NEB","canonical_record":{"source":{"id":"2405.17505","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-26T07:01:33Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"2b3ccabaf987e4aded3177f7854c7ae7bd9224b86f450ddf3eeb7ad2a2374e34","abstract_canon_sha256":"ef58892762f73df0c53a7e4cf2a1546742786fb10a1f13ccd6d64b2e85ea3fae"},"schema_version":"1.0"},"canonical_sha256":"bda26f34815fa14800318d194de739028002e3949d9a35bd86674954ac3bb9d9","source":{"kind":"arxiv","id":"2405.17505","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.17505","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"arxiv_version","alias_value":"2405.17505v1","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.17505","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"pith_short_12","alias_value":"XWRG6NEBL6QU","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"pith_short_16","alias_value":"XWRG6NEBL6QUQABR","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"pith_short_8","alias_value":"XWRG6NEB","created_at":"2026-07-05T08:24:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XWRG6NEBL6QUQABRRUMU3ZZZAK","target":"record","payload":{"canonical_record":{"source":{"id":"2405.17505","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-26T07:01:33Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"2b3ccabaf987e4aded3177f7854c7ae7bd9224b86f450ddf3eeb7ad2a2374e34","abstract_canon_sha256":"ef58892762f73df0c53a7e4cf2a1546742786fb10a1f13ccd6d64b2e85ea3fae"},"schema_version":"1.0"},"canonical_sha256":"bda26f34815fa14800318d194de739028002e3949d9a35bd86674954ac3bb9d9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:24:07.749549Z","signature_b64":"A8gV73YvQRbQqhjLepIw4f/7t1jJgUGz4gMqDHRZt7/lZ0p2ErTNm3f+4pKZ9tSJh4NzkoM3IvlNjzCviRkcDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bda26f34815fa14800318d194de739028002e3949d9a35bd86674954ac3bb9d9","last_reissued_at":"2026-07-05T08:24:07.749119Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:24:07.749119Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.17505","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":"2026-07-05T08:24:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"adpePLn6jKzi8uZc0xtngNL7CvE1secZbv3w577R6qb8CoTaz3eNyxVKe8KYskJoBbDTlgI2yM8fe2SENqeeDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T18:32:58.985349Z"},"content_sha256":"a4eb36fa4f838013e144991372a25ae2f797fbae24f0527f8e91d2c106d99eb6","schema_version":"1.0","event_id":"sha256:a4eb36fa4f838013e144991372a25ae2f797fbae24f0527f8e91d2c106d99eb6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XWRG6NEBL6QUQABRRUMU3ZZZAK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Predicting Rental Price of Lane Houses in Shanghai with Machine Learning Methods and Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Shijing Si, Tingting Chen","submitted_at":"2024-05-26T07:01:33Z","abstract_excerpt":"Housing has emerged as a crucial concern among young individuals residing in major cities, including Shanghai. Given the unprecedented surge in property prices in this metropolis, young people have increasingly resorted to the rental market to address their housing needs. This study utilizes five traditional machine learning methods: multiple linear regression (MLR), ridge regression (RR), lasso regression (LR), decision tree (DT), and random forest (RF), along with a Large Language Model (LLM) approach using ChatGPT, for predicting the rental prices of lane houses in Shanghai. It applies thes"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.17505","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/2405.17505/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":"2026-07-05T08:24:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KY7jL9QsBCQTlBJky5UEAqwi3AA/vPO7nBtDp0mTwz/sfjU5AUu2hXXHxc+MH34PDOp0lDc544u3Y7WksiCSDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T18:32:58.985859Z"},"content_sha256":"80fa7eaee64105372243912e76f11a4075b579778a0739471ae268ba1715951f","schema_version":"1.0","event_id":"sha256:80fa7eaee64105372243912e76f11a4075b579778a0739471ae268ba1715951f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XWRG6NEBL6QUQABRRUMU3ZZZAK/bundle.json","state_url":"https://pith.science/pith/XWRG6NEBL6QUQABRRUMU3ZZZAK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XWRG6NEBL6QUQABRRUMU3ZZZAK/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":"2026-08-20T18:32:58Z","links":{"resolver":"https://pith.science/pith/XWRG6NEBL6QUQABRRUMU3ZZZAK","bundle":"https://pith.science/pith/XWRG6NEBL6QUQABRRUMU3ZZZAK/bundle.json","state":"https://pith.science/pith/XWRG6NEBL6QUQABRRUMU3ZZZAK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XWRG6NEBL6QUQABRRUMU3ZZZAK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XWRG6NEBL6QUQABRRUMU3ZZZAK","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":"ef58892762f73df0c53a7e4cf2a1546742786fb10a1f13ccd6d64b2e85ea3fae","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-26T07:01:33Z","title_canon_sha256":"2b3ccabaf987e4aded3177f7854c7ae7bd9224b86f450ddf3eeb7ad2a2374e34"},"schema_version":"1.0","source":{"id":"2405.17505","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.17505","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"arxiv_version","alias_value":"2405.17505v1","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.17505","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"pith_short_12","alias_value":"XWRG6NEBL6QU","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"pith_short_16","alias_value":"XWRG6NEBL6QUQABR","created_at":"2026-07-05T08:24:07Z"},{"alias_kind":"pith_short_8","alias_value":"XWRG6NEB","created_at":"2026-07-05T08:24:07Z"}],"graph_snapshots":[{"event_id":"sha256:80fa7eaee64105372243912e76f11a4075b579778a0739471ae268ba1715951f","target":"graph","created_at":"2026-07-05T08:24:07Z","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/2405.17505/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Housing has emerged as a crucial concern among young individuals residing in major cities, including Shanghai. Given the unprecedented surge in property prices in this metropolis, young people have increasingly resorted to the rental market to address their housing needs. This study utilizes five traditional machine learning methods: multiple linear regression (MLR), ridge regression (RR), lasso regression (LR), decision tree (DT), and random forest (RF), along with a Large Language Model (LLM) approach using ChatGPT, for predicting the rental prices of lane houses in Shanghai. It applies thes","authors_text":"Shijing Si, Tingting Chen","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-26T07:01:33Z","title":"Predicting Rental Price of Lane Houses in Shanghai with Machine Learning Methods and Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.17505","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:a4eb36fa4f838013e144991372a25ae2f797fbae24f0527f8e91d2c106d99eb6","target":"record","created_at":"2026-07-05T08:24:07Z","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":"ef58892762f73df0c53a7e4cf2a1546742786fb10a1f13ccd6d64b2e85ea3fae","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-26T07:01:33Z","title_canon_sha256":"2b3ccabaf987e4aded3177f7854c7ae7bd9224b86f450ddf3eeb7ad2a2374e34"},"schema_version":"1.0","source":{"id":"2405.17505","kind":"arxiv","version":1}},"canonical_sha256":"bda26f34815fa14800318d194de739028002e3949d9a35bd86674954ac3bb9d9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bda26f34815fa14800318d194de739028002e3949d9a35bd86674954ac3bb9d9","first_computed_at":"2026-07-05T08:24:07.749119Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:24:07.749119Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A8gV73YvQRbQqhjLepIw4f/7t1jJgUGz4gMqDHRZt7/lZ0p2ErTNm3f+4pKZ9tSJh4NzkoM3IvlNjzCviRkcDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:24:07.749549Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.17505","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a4eb36fa4f838013e144991372a25ae2f797fbae24f0527f8e91d2c106d99eb6","sha256:80fa7eaee64105372243912e76f11a4075b579778a0739471ae268ba1715951f"],"state_sha256":"fa204f632fdc01d678e2c14edb5f6dec2e21f26da343bc60b0a0857bcac1e558"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2eXkMI6RNfxIJLmBN1o0mynfj+9Gy1Ql56IFiOCuzF9yzialoTcQs2QghA/yRe2OJ30TBaAH25xW1O59qIM6DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T18:32:58.992129Z","bundle_sha256":"bc26482220f06c755b5040bc4905fc28df5a4a5a2cca10094971cf8b247d85da"}}