{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VT6SWCQ72D72FUCPZJBCXSJYWH","short_pith_number":"pith:VT6SWCQ7","canonical_record":{"source":{"id":"2507.08367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:28:49Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"e22e0c58966d630f94e19ad17ac92d8fc32138b9b4eb10179ee3e4a4b700b71a","abstract_canon_sha256":"79a6dba1871cb057ef63534ed1868b8673884b60ddb779a10241ede420eb25b0"},"schema_version":"1.0"},"canonical_sha256":"acfd2b0a1fd0ffa2d04fca422bc938b1d81e01307206b5f7a7fa7c3d4a19f438","source":{"kind":"arxiv","id":"2507.08367","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.08367","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"arxiv_version","alias_value":"2507.08367v1","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08367","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"pith_short_12","alias_value":"VT6SWCQ72D72","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"pith_short_16","alias_value":"VT6SWCQ72D72FUCP","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"pith_short_8","alias_value":"VT6SWCQ7","created_at":"2026-07-05T11:35:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VT6SWCQ72D72FUCPZJBCXSJYWH","target":"record","payload":{"canonical_record":{"source":{"id":"2507.08367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:28:49Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"e22e0c58966d630f94e19ad17ac92d8fc32138b9b4eb10179ee3e4a4b700b71a","abstract_canon_sha256":"79a6dba1871cb057ef63534ed1868b8673884b60ddb779a10241ede420eb25b0"},"schema_version":"1.0"},"canonical_sha256":"acfd2b0a1fd0ffa2d04fca422bc938b1d81e01307206b5f7a7fa7c3d4a19f438","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:35:22.170154Z","signature_b64":"cUMWCoVof2ocfAnRvVviWgFS6SXISVxoPA5XlCLxOMsxOSlNxbQtAJIHUgjStUAGFKQ2k1kqZ5B4VC0wttK9CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"acfd2b0a1fd0ffa2d04fca422bc938b1d81e01307206b5f7a7fa7c3d4a19f438","last_reissued_at":"2026-07-05T11:35:22.169689Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:35:22.169689Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.08367","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":"2026-07-05T11:35:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D5fBBxSUavRkHBrW1arXA4QIiAbTwjx0spw0cL4z6d/OCmgyO870n0GeWweVyHXELQNSAzw4R7P635vnjdb/CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T22:18:58.508970Z"},"content_sha256":"af47e5eb4f890a561e4dbacb45da432cdf965577b671300bb9fabb0bba4dd7d7","schema_version":"1.0","event_id":"sha256:af47e5eb4f890a561e4dbacb45da432cdf965577b671300bb9fabb0bba4dd7d7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VT6SWCQ72D72FUCPZJBCXSJYWH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.CV","authors_text":"Asuka Harada, Hitoshi Kanamori, Linjing Jiang, Nihan Karatas, Takahiro Tanaka, Yuki Yoshihara","submitted_at":"2025-07-11T07:28:49Z","abstract_excerpt":"This study investigates the potential of a multimodal large language model (LLM), specifically ChatGPT-4o, to perform human-like interpretations of traffic scenes using static dashcam images. Herein, we focus on three judgment tasks relevant to elderly driver assessments: evaluating traffic density, assessing intersection visibility, and recognizing stop signs recognition. These tasks require contextual reasoning rather than simple object detection. Using zero-shot, few-shot, and multi-shot prompting strategies, we evaluated the performance of the model with human annotations serving as the re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08367","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/2507.08367/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":"2026-07-05T11:35:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/HB4pN25Qs4fItxvR7CP5YUh+zAN8PvNKgC2W3v/PZ8hPyAgOo+kq3DVIk0PH72EXPoI7T350JA4SWH534Y2BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T22:18:58.509465Z"},"content_sha256":"858446d6945c83bce3988c10cdb4852d2431d434b7fad8e6cff8bd44616ca771","schema_version":"1.0","event_id":"sha256:858446d6945c83bce3988c10cdb4852d2431d434b7fad8e6cff8bd44616ca771"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VT6SWCQ72D72FUCPZJBCXSJYWH/bundle.json","state_url":"https://pith.science/pith/VT6SWCQ72D72FUCPZJBCXSJYWH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VT6SWCQ72D72FUCPZJBCXSJYWH/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":"2026-08-08T22:18:58Z","links":{"resolver":"https://pith.science/pith/VT6SWCQ72D72FUCPZJBCXSJYWH","bundle":"https://pith.science/pith/VT6SWCQ72D72FUCPZJBCXSJYWH/bundle.json","state":"https://pith.science/pith/VT6SWCQ72D72FUCPZJBCXSJYWH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VT6SWCQ72D72FUCPZJBCXSJYWH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VT6SWCQ72D72FUCPZJBCXSJYWH","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":"79a6dba1871cb057ef63534ed1868b8673884b60ddb779a10241ede420eb25b0","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:28:49Z","title_canon_sha256":"e22e0c58966d630f94e19ad17ac92d8fc32138b9b4eb10179ee3e4a4b700b71a"},"schema_version":"1.0","source":{"id":"2507.08367","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.08367","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"arxiv_version","alias_value":"2507.08367v1","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08367","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"pith_short_12","alias_value":"VT6SWCQ72D72","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"pith_short_16","alias_value":"VT6SWCQ72D72FUCP","created_at":"2026-07-05T11:35:22Z"},{"alias_kind":"pith_short_8","alias_value":"VT6SWCQ7","created_at":"2026-07-05T11:35:22Z"}],"graph_snapshots":[{"event_id":"sha256:858446d6945c83bce3988c10cdb4852d2431d434b7fad8e6cff8bd44616ca771","target":"graph","created_at":"2026-07-05T11:35:22Z","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/2507.08367/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study investigates the potential of a multimodal large language model (LLM), specifically ChatGPT-4o, to perform human-like interpretations of traffic scenes using static dashcam images. Herein, we focus on three judgment tasks relevant to elderly driver assessments: evaluating traffic density, assessing intersection visibility, and recognizing stop signs recognition. These tasks require contextual reasoning rather than simple object detection. Using zero-shot, few-shot, and multi-shot prompting strategies, we evaluated the performance of the model with human annotations serving as the re","authors_text":"Asuka Harada, Hitoshi Kanamori, Linjing Jiang, Nihan Karatas, Takahiro Tanaka, Yuki Yoshihara","cross_cats":["cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:28:49Z","title":"Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08367","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:af47e5eb4f890a561e4dbacb45da432cdf965577b671300bb9fabb0bba4dd7d7","target":"record","created_at":"2026-07-05T11:35:22Z","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":"79a6dba1871cb057ef63534ed1868b8673884b60ddb779a10241ede420eb25b0","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:28:49Z","title_canon_sha256":"e22e0c58966d630f94e19ad17ac92d8fc32138b9b4eb10179ee3e4a4b700b71a"},"schema_version":"1.0","source":{"id":"2507.08367","kind":"arxiv","version":1}},"canonical_sha256":"acfd2b0a1fd0ffa2d04fca422bc938b1d81e01307206b5f7a7fa7c3d4a19f438","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"acfd2b0a1fd0ffa2d04fca422bc938b1d81e01307206b5f7a7fa7c3d4a19f438","first_computed_at":"2026-07-05T11:35:22.169689Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:35:22.169689Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cUMWCoVof2ocfAnRvVviWgFS6SXISVxoPA5XlCLxOMsxOSlNxbQtAJIHUgjStUAGFKQ2k1kqZ5B4VC0wttK9CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:35:22.170154Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.08367","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af47e5eb4f890a561e4dbacb45da432cdf965577b671300bb9fabb0bba4dd7d7","sha256:858446d6945c83bce3988c10cdb4852d2431d434b7fad8e6cff8bd44616ca771"],"state_sha256":"4795f4d64681d34ed02b4b3e739503a51e5ff5acb087f364b9b3e83ef9e38059"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nmEaWJswbGbwdRQeKa7c5UIZsEzD0opOj8H9Ff3K40OvsTYj4wpnu8+VHYaw7eWQd4Zliqq0Tc0kShtM5avyAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T22:18:58.514643Z","bundle_sha256":"b664230b2c2630e652b58f8fe11fc79bcba1e83e8a894396e8d8fb9c5999ffe6"}}