{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:D44KHIEU6QPHZUC5PUA4AWPIC2","short_pith_number":"pith:D44KHIEU","canonical_record":{"source":{"id":"2608.13369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-08-13T15:33:12Z","cross_cats_sorted":[],"title_canon_sha256":"489d0fbc1c22a89dcd23e4eabb67918810337ce33c28ef931a60a89394f1616f","abstract_canon_sha256":"04d3bcf2046857471da768d80fa974c0fa4c38e0491e8cebf2306baa66ed1b9d"},"schema_version":"1.0"},"canonical_sha256":"1f38a3a094f41e7cd05d7d01c059e816b0f2e59ae87fd388765307065d948a16","source":{"kind":"arxiv","id":"2608.13369","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.13369","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"arxiv_version","alias_value":"2608.13369v1","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.13369","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"pith_short_12","alias_value":"D44KHIEU6QPH","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"pith_short_16","alias_value":"D44KHIEU6QPHZUC5","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"pith_short_8","alias_value":"D44KHIEU","created_at":"2026-08-14T01:04:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:D44KHIEU6QPHZUC5PUA4AWPIC2","target":"record","payload":{"canonical_record":{"source":{"id":"2608.13369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-08-13T15:33:12Z","cross_cats_sorted":[],"title_canon_sha256":"489d0fbc1c22a89dcd23e4eabb67918810337ce33c28ef931a60a89394f1616f","abstract_canon_sha256":"04d3bcf2046857471da768d80fa974c0fa4c38e0491e8cebf2306baa66ed1b9d"},"schema_version":"1.0"},"canonical_sha256":"1f38a3a094f41e7cd05d7d01c059e816b0f2e59ae87fd388765307065d948a16","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-14T01:04:18.647061Z","signature_b64":"mTaLUTlycfnC//qMiVNtJFeFw5uFzMkS0FPVKK4gbQ4COj7HkPYr2+rRU0UFjotS7Tqy19L7RiDe9TcaAydQAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f38a3a094f41e7cd05d7d01c059e816b0f2e59ae87fd388765307065d948a16","last_reissued_at":"2026-08-14T01:04:18.645196Z","signature_status":"signed_v1","first_computed_at":"2026-08-14T01:04:18.645196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.13369","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":"2026-08-14T01:04:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SdPaMB/Jaii/IMoM7559Cf5UVKIJ4RQMwImRIIVpX3uek/N9opRg4k34gKx0ESUFcZOBxlixGobwFFYZTv8JCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T02:58:42.834546Z"},"content_sha256":"3e864d0ad857e07b759883f45f5b79a65c28cc6b0948c85e0506be8bd588bc2d","schema_version":"1.0","event_id":"sha256:3e864d0ad857e07b759883f45f5b79a65c28cc6b0948c85e0506be8bd588bc2d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:D44KHIEU6QPHZUC5PUA4AWPIC2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Credible, Not Always Correct: How Reddit Users Verify AI-Generated Legal Advice","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CY","authors_text":"Dhyey Mehta, Rebecca Owens, Stergios Aidinlis, Tu\\u{g}rulcan Elmas, Yusuf M\\\"ucahit \\c{C}etinkaya","submitted_at":"2026-08-13T15:33:12Z","abstract_excerpt":"Large language models (LLMs) are increasingly used by laypeople to resolve real legal problems, against a backdrop of persistent access-to-justice deficits. This article presents evidence that the practical force of AI-generated legal advice depends not on its accuracy but on the social production of its credibility. While existing research has assessed the accuracy of legal AI, less is known about how machine-generated guidance is verified and made credible enough for lay users to act on. Drawing on a dual-method analysis of 153 Reddit narratives and 5,341 community reactions, this article ma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.13369","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/2608.13369/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":"2026-08-14T01:04:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ib2HPuqK5bWjBAnHv4/zoxw24sZbWK47yfmhBWh7EufvDMI15NXC0+2R+ZXqTEy92p5rAgkoQQFvoepCbhruAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T02:58:42.835259Z"},"content_sha256":"3d57ae708dd672e09dc8103290e9f51c068c55195b41f5a1c908d244e61653fe","schema_version":"1.0","event_id":"sha256:3d57ae708dd672e09dc8103290e9f51c068c55195b41f5a1c908d244e61653fe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D44KHIEU6QPHZUC5PUA4AWPIC2/bundle.json","state_url":"https://pith.science/pith/D44KHIEU6QPHZUC5PUA4AWPIC2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D44KHIEU6QPHZUC5PUA4AWPIC2/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":"2026-08-16T02:58:42Z","links":{"resolver":"https://pith.science/pith/D44KHIEU6QPHZUC5PUA4AWPIC2","bundle":"https://pith.science/pith/D44KHIEU6QPHZUC5PUA4AWPIC2/bundle.json","state":"https://pith.science/pith/D44KHIEU6QPHZUC5PUA4AWPIC2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D44KHIEU6QPHZUC5PUA4AWPIC2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:D44KHIEU6QPHZUC5PUA4AWPIC2","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":"04d3bcf2046857471da768d80fa974c0fa4c38e0491e8cebf2306baa66ed1b9d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-08-13T15:33:12Z","title_canon_sha256":"489d0fbc1c22a89dcd23e4eabb67918810337ce33c28ef931a60a89394f1616f"},"schema_version":"1.0","source":{"id":"2608.13369","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.13369","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"arxiv_version","alias_value":"2608.13369v1","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.13369","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"pith_short_12","alias_value":"D44KHIEU6QPH","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"pith_short_16","alias_value":"D44KHIEU6QPHZUC5","created_at":"2026-08-14T01:04:18Z"},{"alias_kind":"pith_short_8","alias_value":"D44KHIEU","created_at":"2026-08-14T01:04:18Z"}],"graph_snapshots":[{"event_id":"sha256:3d57ae708dd672e09dc8103290e9f51c068c55195b41f5a1c908d244e61653fe","target":"graph","created_at":"2026-08-14T01:04:18Z","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/2608.13369/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are increasingly used by laypeople to resolve real legal problems, against a backdrop of persistent access-to-justice deficits. This article presents evidence that the practical force of AI-generated legal advice depends not on its accuracy but on the social production of its credibility. While existing research has assessed the accuracy of legal AI, less is known about how machine-generated guidance is verified and made credible enough for lay users to act on. Drawing on a dual-method analysis of 153 Reddit narratives and 5,341 community reactions, this article ma","authors_text":"Dhyey Mehta, Rebecca Owens, Stergios Aidinlis, Tu\\u{g}rulcan Elmas, Yusuf M\\\"ucahit \\c{C}etinkaya","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-08-13T15:33:12Z","title":"Credible, Not Always Correct: How Reddit Users Verify AI-Generated Legal Advice"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.13369","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":"sha256:3e864d0ad857e07b759883f45f5b79a65c28cc6b0948c85e0506be8bd588bc2d","target":"record","created_at":"2026-08-14T01:04:18Z","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":"04d3bcf2046857471da768d80fa974c0fa4c38e0491e8cebf2306baa66ed1b9d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2026-08-13T15:33:12Z","title_canon_sha256":"489d0fbc1c22a89dcd23e4eabb67918810337ce33c28ef931a60a89394f1616f"},"schema_version":"1.0","source":{"id":"2608.13369","kind":"arxiv","version":1}},"canonical_sha256":"1f38a3a094f41e7cd05d7d01c059e816b0f2e59ae87fd388765307065d948a16","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f38a3a094f41e7cd05d7d01c059e816b0f2e59ae87fd388765307065d948a16","first_computed_at":"2026-08-14T01:04:18.645196Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-14T01:04:18.645196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mTaLUTlycfnC//qMiVNtJFeFw5uFzMkS0FPVKK4gbQ4COj7HkPYr2+rRU0UFjotS7Tqy19L7RiDe9TcaAydQAw==","signature_status":"signed_v1","signed_at":"2026-08-14T01:04:18.647061Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.13369","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e864d0ad857e07b759883f45f5b79a65c28cc6b0948c85e0506be8bd588bc2d","sha256:3d57ae708dd672e09dc8103290e9f51c068c55195b41f5a1c908d244e61653fe"],"state_sha256":"2294cf8ca94fe29a44c742690dba60932818b7f37defea2c1cb4b21f66c74ad4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dIxlruyCFLg9lLgaqVvN25NUcIsolluQeRpWalzCHjPqnl9fGmyQM+oJTHkaTLWwbxSpOhTEEOr3EML/Y3CSBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T02:58:42.839167Z","bundle_sha256":"6759f675aca2425528ec2306806b12bd56b4f3a54ab94f2177e9ddfe6d6570e6"}}