{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SHLFHY3ELTE2R5NBLLHJU37OWK","short_pith_number":"pith:SHLFHY3E","canonical_record":{"source":{"id":"2508.00963","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T14:12:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"da85c01b266a6d6725a01ff974bdfc8c1e7c2135100b87603859993e8ba3dab1","abstract_canon_sha256":"b73242d264efefaca51d87cba969ab205b554f9423841f9562cbd1bbd601e198"},"schema_version":"1.0"},"canonical_sha256":"91d653e3645cc9a8f5a15ace9a6feeb2b1f6698f45381072a338777b7ca9d85f","source":{"kind":"arxiv","id":"2508.00963","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.00963","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"arxiv_version","alias_value":"2508.00963v1","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.00963","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"pith_short_12","alias_value":"SHLFHY3ELTE2","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"pith_short_16","alias_value":"SHLFHY3ELTE2R5NB","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"pith_short_8","alias_value":"SHLFHY3E","created_at":"2026-07-05T11:47:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SHLFHY3ELTE2R5NBLLHJU37OWK","target":"record","payload":{"canonical_record":{"source":{"id":"2508.00963","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T14:12:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"da85c01b266a6d6725a01ff974bdfc8c1e7c2135100b87603859993e8ba3dab1","abstract_canon_sha256":"b73242d264efefaca51d87cba969ab205b554f9423841f9562cbd1bbd601e198"},"schema_version":"1.0"},"canonical_sha256":"91d653e3645cc9a8f5a15ace9a6feeb2b1f6698f45381072a338777b7ca9d85f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:47:30.918575Z","signature_b64":"IITSsyQ1LgFKbx+J8/E6LfuqTgBXAzc5rrvZLgakA40NxNCvxurluGcv9AD1mdSQCAl321KoJZxfvbXLmLuDAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"91d653e3645cc9a8f5a15ace9a6feeb2b1f6698f45381072a338777b7ca9d85f","last_reissued_at":"2026-07-05T11:47:30.918086Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:47:30.918086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.00963","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":"2026-07-05T11:47:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6Zl6hF5veCCIXLi7wWRvkmx4HQTTfkPT02LoCcUmMcuaS5Q4auFV3MptVtA6d7kQ22bwhily/BNsd5ztxBPNAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:00:50.420369Z"},"content_sha256":"727a4fb816933cb1e77d8f6c2319cb58ce7f3599229e1cb1ef3f21fc440a012c","schema_version":"1.0","event_id":"sha256:727a4fb816933cb1e77d8f6c2319cb58ce7f3599229e1cb1ef3f21fc440a012c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SHLFHY3ELTE2R5NBLLHJU37OWK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Rethinking Multimodality: Optimizing Multimodal Deep Learning for Biomedical Signal Classification","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Alex Wong, Timothy Oladunni","submitted_at":"2025-08-01T14:12:10Z","abstract_excerpt":"This study proposes a novel perspective on multimodal deep learning for biomedical signal classification, systematically analyzing how complementary feature domains impact model performance. While fusing multiple domains often presumes enhanced accuracy, this work demonstrates that adding modalities can yield diminishing returns, as not all fusions are inherently advantageous. To validate this, five deep learning models were designed, developed, and rigorously evaluated: three unimodal (1D-CNN for time, 2D-CNN for time-frequency, and 1D-CNN-Transformer for frequency) and two multimodal (Hybrid"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.00963","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/2508.00963/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":"2026-07-05T11:47:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PdcM1/BX4bbPzVsFcTY2eIsHNdsr6nwXiADumId5NgoqxoapCWPWUdvfLJOldLMb7ZGe5rUv/UMqEeZLk7npCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:00:50.421159Z"},"content_sha256":"7718a67b1e4bd73e710756eb0a087703489f2be28d1b8c6fc8bf88c5e0df811c","schema_version":"1.0","event_id":"sha256:7718a67b1e4bd73e710756eb0a087703489f2be28d1b8c6fc8bf88c5e0df811c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SHLFHY3ELTE2R5NBLLHJU37OWK/bundle.json","state_url":"https://pith.science/pith/SHLFHY3ELTE2R5NBLLHJU37OWK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SHLFHY3ELTE2R5NBLLHJU37OWK/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":"2026-08-14T08:00:50Z","links":{"resolver":"https://pith.science/pith/SHLFHY3ELTE2R5NBLLHJU37OWK","bundle":"https://pith.science/pith/SHLFHY3ELTE2R5NBLLHJU37OWK/bundle.json","state":"https://pith.science/pith/SHLFHY3ELTE2R5NBLLHJU37OWK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SHLFHY3ELTE2R5NBLLHJU37OWK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SHLFHY3ELTE2R5NBLLHJU37OWK","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":"b73242d264efefaca51d87cba969ab205b554f9423841f9562cbd1bbd601e198","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T14:12:10Z","title_canon_sha256":"da85c01b266a6d6725a01ff974bdfc8c1e7c2135100b87603859993e8ba3dab1"},"schema_version":"1.0","source":{"id":"2508.00963","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.00963","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"arxiv_version","alias_value":"2508.00963v1","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.00963","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"pith_short_12","alias_value":"SHLFHY3ELTE2","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"pith_short_16","alias_value":"SHLFHY3ELTE2R5NB","created_at":"2026-07-05T11:47:30Z"},{"alias_kind":"pith_short_8","alias_value":"SHLFHY3E","created_at":"2026-07-05T11:47:30Z"}],"graph_snapshots":[{"event_id":"sha256:7718a67b1e4bd73e710756eb0a087703489f2be28d1b8c6fc8bf88c5e0df811c","target":"graph","created_at":"2026-07-05T11:47:30Z","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/2508.00963/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study proposes a novel perspective on multimodal deep learning for biomedical signal classification, systematically analyzing how complementary feature domains impact model performance. While fusing multiple domains often presumes enhanced accuracy, this work demonstrates that adding modalities can yield diminishing returns, as not all fusions are inherently advantageous. To validate this, five deep learning models were designed, developed, and rigorously evaluated: three unimodal (1D-CNN for time, 2D-CNN for time-frequency, and 1D-CNN-Transformer for frequency) and two multimodal (Hybrid","authors_text":"Alex Wong, Timothy Oladunni","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T14:12:10Z","title":"Rethinking Multimodality: Optimizing Multimodal Deep Learning for Biomedical Signal Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.00963","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":"sha256:727a4fb816933cb1e77d8f6c2319cb58ce7f3599229e1cb1ef3f21fc440a012c","target":"record","created_at":"2026-07-05T11:47:30Z","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":"b73242d264efefaca51d87cba969ab205b554f9423841f9562cbd1bbd601e198","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T14:12:10Z","title_canon_sha256":"da85c01b266a6d6725a01ff974bdfc8c1e7c2135100b87603859993e8ba3dab1"},"schema_version":"1.0","source":{"id":"2508.00963","kind":"arxiv","version":1}},"canonical_sha256":"91d653e3645cc9a8f5a15ace9a6feeb2b1f6698f45381072a338777b7ca9d85f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"91d653e3645cc9a8f5a15ace9a6feeb2b1f6698f45381072a338777b7ca9d85f","first_computed_at":"2026-07-05T11:47:30.918086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:47:30.918086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IITSsyQ1LgFKbx+J8/E6LfuqTgBXAzc5rrvZLgakA40NxNCvxurluGcv9AD1mdSQCAl321KoJZxfvbXLmLuDAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:47:30.918575Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.00963","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:727a4fb816933cb1e77d8f6c2319cb58ce7f3599229e1cb1ef3f21fc440a012c","sha256:7718a67b1e4bd73e710756eb0a087703489f2be28d1b8c6fc8bf88c5e0df811c"],"state_sha256":"c3d3851ee4034f5279197a19e689aafb99e1122879e38eb07eeaf19590c906a4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y/TQv6f5usJhx6XY1/vwFhRIB3K50/4Ke7gRzdgZy4TNtxpiQ/hLnvs1h3qmqfP3MWMFdZolhJRN/zAS3m6UDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T08:00:50.497131Z","bundle_sha256":"250ad9ac28523b8722e68f91fb1843be992e6adf929bb7f78f133ef22fea1a91"}}