{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:MMUV3BN7HDM5DHINXZCVHVFRBW","short_pith_number":"pith:MMUV3BN7","schema_version":"1.0","canonical_sha256":"63295d85bf38d9d19d0dbe4553d4b10d8ed086bff1b539cb36fc511b986a4d5a","source":{"kind":"arxiv","id":"2505.23822","version":3},"attestation_state":"computed","paper":{"title":"Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CL","authors_text":"Christopher Lucasius, Deepa Kundur, Jacob Vorstman, Madison Aitken, Mai Ali, Marco Battaglia, Peter Szatmari, Tanmay P. Patel","submitted_at":"2025-05-28T04:07:17Z","abstract_excerpt":"Speech is a noninvasive digital phenotype that can offer valuable insights into mental health conditions, but it is often treated as a single modality. In contrast, we propose the treatment of patient speech data as a trimodal multimedia data source for depression detection. This study explores the potential of large language model-based architectures for speech-based depression prediction in a multimodal regime that integrates speech-derived text, acoustic landmarks, and vocal biomarkers. Adolescent depression presents a significant challenge and is often comorbid with multiple disorders, suc"},"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":"2505.23822","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-28T04:07:17Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"4dacade19aaba79290268f65923cf5924352f59d2293ab4dd7eb285d5bfee3c9","abstract_canon_sha256":"0a6aed7fe8cd33cf72ed4fba890e2af13c45ab9d7f60019f58524ff598088f7a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:41:42.394904Z","signature_b64":"6R6r39FmWlK51wFSefQPYGhoN/NX+HCSXEIo1BbifXDhQM9Fw4TVPBu4eTPxvK8xccw9aq9riUYYL38VnuRkDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"63295d85bf38d9d19d0dbe4553d4b10d8ed086bff1b539cb36fc511b986a4d5a","last_reissued_at":"2026-07-05T11:41:42.394409Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:41:42.394409Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CL","authors_text":"Christopher Lucasius, Deepa Kundur, Jacob Vorstman, Madison Aitken, Mai Ali, Marco Battaglia, Peter Szatmari, Tanmay P. Patel","submitted_at":"2025-05-28T04:07:17Z","abstract_excerpt":"Speech is a noninvasive digital phenotype that can offer valuable insights into mental health conditions, but it is often treated as a single modality. In contrast, we propose the treatment of patient speech data as a trimodal multimedia data source for depression detection. This study explores the potential of large language model-based architectures for speech-based depression prediction in a multimodal regime that integrates speech-derived text, acoustic landmarks, and vocal biomarkers. Adolescent depression presents a significant challenge and is often comorbid with multiple disorders, suc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.23822","kind":"arxiv","version":3},"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/2505.23822/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":"2505.23822","created_at":"2026-07-05T11:41:42.394469+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.23822v3","created_at":"2026-07-05T11:41:42.394469+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.23822","created_at":"2026-07-05T11:41:42.394469+00:00"},{"alias_kind":"pith_short_12","alias_value":"MMUV3BN7HDM5","created_at":"2026-07-05T11:41:42.394469+00:00"},{"alias_kind":"pith_short_16","alias_value":"MMUV3BN7HDM5DHIN","created_at":"2026-07-05T11:41:42.394469+00:00"},{"alias_kind":"pith_short_8","alias_value":"MMUV3BN7","created_at":"2026-07-05T11:41:42.394469+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/MMUV3BN7HDM5DHINXZCVHVFRBW","json":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW.json","graph_json":"https://pith.science/api/pith-number/MMUV3BN7HDM5DHINXZCVHVFRBW/graph.json","events_json":"https://pith.science/api/pith-number/MMUV3BN7HDM5DHINXZCVHVFRBW/events.json","paper":"https://pith.science/paper/MMUV3BN7"},"agent_actions":{"view_html":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW","download_json":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW.json","view_paper":"https://pith.science/paper/MMUV3BN7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.23822&json=true","fetch_graph":"https://pith.science/api/pith-number/MMUV3BN7HDM5DHINXZCVHVFRBW/graph.json","fetch_events":"https://pith.science/api/pith-number/MMUV3BN7HDM5DHINXZCVHVFRBW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW/action/storage_attestation","attest_author":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW/action/author_attestation","sign_citation":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW/action/citation_signature","submit_replication":"https://pith.science/pith/MMUV3BN7HDM5DHINXZCVHVFRBW/action/replication_record"}},"created_at":"2026-07-05T11:41:42.394469+00:00","updated_at":"2026-07-05T11:41:42.394469+00:00"}