{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3XAVTTXRFTA7W35IUY5U6A75NY","short_pith_number":"pith:3XAVTTXR","canonical_record":{"source":{"id":"2508.11285","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-08-15T07:47:10Z","cross_cats_sorted":[],"title_canon_sha256":"b87ce008edfc1f5a94842321c15fe4617520d4a7c1ebecd22052fcb505595ffe","abstract_canon_sha256":"8de351f0b4f890ab44cbe35a19dabd3edeb9ed814cd30239b21cff2ed4dadf37"},"schema_version":"1.0"},"canonical_sha256":"ddc159cef12cc1fb6fa8a63b4f03fd6e0aa9f41e40f13514ff7e2513cef51e0f","source":{"kind":"arxiv","id":"2508.11285","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.11285","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"arxiv_version","alias_value":"2508.11285v1","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.11285","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"pith_short_12","alias_value":"3XAVTTXRFTA7","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"pith_short_16","alias_value":"3XAVTTXRFTA7W35I","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"pith_short_8","alias_value":"3XAVTTXR","created_at":"2026-07-05T11:54:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3XAVTTXRFTA7W35IUY5U6A75NY","target":"record","payload":{"canonical_record":{"source":{"id":"2508.11285","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-08-15T07:47:10Z","cross_cats_sorted":[],"title_canon_sha256":"b87ce008edfc1f5a94842321c15fe4617520d4a7c1ebecd22052fcb505595ffe","abstract_canon_sha256":"8de351f0b4f890ab44cbe35a19dabd3edeb9ed814cd30239b21cff2ed4dadf37"},"schema_version":"1.0"},"canonical_sha256":"ddc159cef12cc1fb6fa8a63b4f03fd6e0aa9f41e40f13514ff7e2513cef51e0f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:54:22.020692Z","signature_b64":"m8RYX6Wyc+u3Vwe77tgkUr3dwr7CaEONMD8ixXV1h7e0E023dRqJFQwKPKx6j9ELxGKEwUsqynbElyrElT0mAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ddc159cef12cc1fb6fa8a63b4f03fd6e0aa9f41e40f13514ff7e2513cef51e0f","last_reissued_at":"2026-07-05T11:54:22.020248Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:54:22.020248Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.11285","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":"2026-07-05T11:54:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZkuMhJ7WfFEocvbhyosT3nf0X+or8BjZ0cEA0SOKvA8IdVuwz8JylecIkFu72w/Ve/Qz6vHz8bB7N3kfOpYBBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:25:47.151683Z"},"content_sha256":"462ea6a06367c9ed31928ade087131bb30c0eae959a788c6665dcac810dd66ee","schema_version":"1.0","event_id":"sha256:462ea6a06367c9ed31928ade087131bb30c0eae959a788c6665dcac810dd66ee"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3XAVTTXRFTA7W35IUY5U6A75NY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AI in Mental Health: Emotional and Sentiment Analysis of Large Language Models' Responses to Depression, Anxiety, and Stress Queries","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Arya VarastehNezhad, Hamed Farbeh, MohammadHossein LotfiNia, Reza Tavasoli, Soroush Elyasi","submitted_at":"2025-08-15T07:47:10Z","abstract_excerpt":"Depression, anxiety, and stress are widespread mental health concerns that increasingly drive individuals to seek information from Large Language Models (LLMs). This study investigates how eight LLMs (Claude Sonnet, Copilot, Gemini Pro, GPT-4o, GPT-4o mini, Llama, Mixtral, and Perplexity) reply to twenty pragmatic questions about depression, anxiety, and stress when those questions are framed for six user profiles (baseline, woman, man, young, old, and university student). The models generated 2,880 answers, which we scored for sentiment and emotions using state-of-the-art tools. Our analysis "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.11285","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/2508.11285/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":"2026-07-05T11:54:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0/DyQ1TxumEg70etfPmET5JixQS0g0bzMsybYRo5LXUzwlmsz9vz2Q+r8Ft0GL4ugL79G97mjHu1z8BeeDXmCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:25:47.152290Z"},"content_sha256":"9b2587498b61dd95ce155b8b94994999e973c19a0ff116897cdf3e24c179fca0","schema_version":"1.0","event_id":"sha256:9b2587498b61dd95ce155b8b94994999e973c19a0ff116897cdf3e24c179fca0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3XAVTTXRFTA7W35IUY5U6A75NY/bundle.json","state_url":"https://pith.science/pith/3XAVTTXRFTA7W35IUY5U6A75NY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3XAVTTXRFTA7W35IUY5U6A75NY/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":"2026-08-09T03:25:47Z","links":{"resolver":"https://pith.science/pith/3XAVTTXRFTA7W35IUY5U6A75NY","bundle":"https://pith.science/pith/3XAVTTXRFTA7W35IUY5U6A75NY/bundle.json","state":"https://pith.science/pith/3XAVTTXRFTA7W35IUY5U6A75NY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3XAVTTXRFTA7W35IUY5U6A75NY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3XAVTTXRFTA7W35IUY5U6A75NY","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":"8de351f0b4f890ab44cbe35a19dabd3edeb9ed814cd30239b21cff2ed4dadf37","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-08-15T07:47:10Z","title_canon_sha256":"b87ce008edfc1f5a94842321c15fe4617520d4a7c1ebecd22052fcb505595ffe"},"schema_version":"1.0","source":{"id":"2508.11285","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.11285","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"arxiv_version","alias_value":"2508.11285v1","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.11285","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"pith_short_12","alias_value":"3XAVTTXRFTA7","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"pith_short_16","alias_value":"3XAVTTXRFTA7W35I","created_at":"2026-07-05T11:54:22Z"},{"alias_kind":"pith_short_8","alias_value":"3XAVTTXR","created_at":"2026-07-05T11:54:22Z"}],"graph_snapshots":[{"event_id":"sha256:9b2587498b61dd95ce155b8b94994999e973c19a0ff116897cdf3e24c179fca0","target":"graph","created_at":"2026-07-05T11:54:22Z","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/2508.11285/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Depression, anxiety, and stress are widespread mental health concerns that increasingly drive individuals to seek information from Large Language Models (LLMs). This study investigates how eight LLMs (Claude Sonnet, Copilot, Gemini Pro, GPT-4o, GPT-4o mini, Llama, Mixtral, and Perplexity) reply to twenty pragmatic questions about depression, anxiety, and stress when those questions are framed for six user profiles (baseline, woman, man, young, old, and university student). The models generated 2,880 answers, which we scored for sentiment and emotions using state-of-the-art tools. Our analysis ","authors_text":"Arya VarastehNezhad, Hamed Farbeh, MohammadHossein LotfiNia, Reza Tavasoli, Soroush Elyasi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-08-15T07:47:10Z","title":"AI in Mental Health: Emotional and Sentiment Analysis of Large Language Models' Responses to Depression, Anxiety, and Stress Queries"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.11285","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":"sha256:462ea6a06367c9ed31928ade087131bb30c0eae959a788c6665dcac810dd66ee","target":"record","created_at":"2026-07-05T11:54:22Z","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":"8de351f0b4f890ab44cbe35a19dabd3edeb9ed814cd30239b21cff2ed4dadf37","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-08-15T07:47:10Z","title_canon_sha256":"b87ce008edfc1f5a94842321c15fe4617520d4a7c1ebecd22052fcb505595ffe"},"schema_version":"1.0","source":{"id":"2508.11285","kind":"arxiv","version":1}},"canonical_sha256":"ddc159cef12cc1fb6fa8a63b4f03fd6e0aa9f41e40f13514ff7e2513cef51e0f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ddc159cef12cc1fb6fa8a63b4f03fd6e0aa9f41e40f13514ff7e2513cef51e0f","first_computed_at":"2026-07-05T11:54:22.020248Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:54:22.020248Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m8RYX6Wyc+u3Vwe77tgkUr3dwr7CaEONMD8ixXV1h7e0E023dRqJFQwKPKx6j9ELxGKEwUsqynbElyrElT0mAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:54:22.020692Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.11285","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:462ea6a06367c9ed31928ade087131bb30c0eae959a788c6665dcac810dd66ee","sha256:9b2587498b61dd95ce155b8b94994999e973c19a0ff116897cdf3e24c179fca0"],"state_sha256":"f70b76f444f760c421ec98ad06f956df68bd90569e695134dd38671f32da1673"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SK+fPJENCrdwDRj6RaFZqv+xjyG5sFCPrfSrPAMdIgP4i/Ut1nYR6BfenfipqD2XPQnsMWgujLlu83K7ukCMBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T03:25:47.157450Z","bundle_sha256":"219ed7c1af04b14b48668d7c4fe40898e689feccdaa4ccaba7f49df0b5fc8200"}}