{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:R6H5I4Z3NKZMO27KIULNZMGPUT","short_pith_number":"pith:R6H5I4Z3","canonical_record":{"source":{"id":"2210.07411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-13T23:24:12Z","cross_cats_sorted":[],"title_canon_sha256":"cc4e610b21df43994dc7994dbcfce52270cd8cfff5272c6cce65f816f81bbf19","abstract_canon_sha256":"e3064fc9fe8063983b0b82c4a71c9db06a732913a6b6f22de77310e21f10c6cd"},"schema_version":"1.0"},"canonical_sha256":"8f8fd4733b6ab2c76bea4516dcb0cfa4ca267c894e941507361057449ab6cf3c","source":{"kind":"arxiv","id":"2210.07411","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.07411","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"arxiv_version","alias_value":"2210.07411v2","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.07411","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"pith_short_12","alias_value":"R6H5I4Z3NKZM","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"pith_short_16","alias_value":"R6H5I4Z3NKZMO27K","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"pith_short_8","alias_value":"R6H5I4Z3","created_at":"2026-07-05T05:33:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:R6H5I4Z3NKZMO27KIULNZMGPUT","target":"record","payload":{"canonical_record":{"source":{"id":"2210.07411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-13T23:24:12Z","cross_cats_sorted":[],"title_canon_sha256":"cc4e610b21df43994dc7994dbcfce52270cd8cfff5272c6cce65f816f81bbf19","abstract_canon_sha256":"e3064fc9fe8063983b0b82c4a71c9db06a732913a6b6f22de77310e21f10c6cd"},"schema_version":"1.0"},"canonical_sha256":"8f8fd4733b6ab2c76bea4516dcb0cfa4ca267c894e941507361057449ab6cf3c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:33:19.441981Z","signature_b64":"sd2dRAl6rDR6vEmfvM1tAD1XY2Tp05tfGpder+d/cF2jCYNH6OXinBgm9xCggOeePKE1y1VKztOfd4aj0FKDAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8f8fd4733b6ab2c76bea4516dcb0cfa4ca267c894e941507361057449ab6cf3c","last_reissued_at":"2026-07-05T05:33:19.441479Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:33:19.441479Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.07411","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:33:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n7vPC+VsToxGHZ0g7YwiFQPDQSwujkntbvPyaNqpl4CqFYqiu9a/TRBIPQIu4qwZF9N3UnbNVqrCcBVBJIaJDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T05:27:38.752045Z"},"content_sha256":"f748bd93b8b37f37f193e2a08e77dc5f2ff0c794e7d8d59742b2f73f85a22501","schema_version":"1.0","event_id":"sha256:f748bd93b8b37f37f193e2a08e77dc5f2ff0c794e7d8d59742b2f73f85a22501"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:R6H5I4Z3NKZMO27KIULNZMGPUT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chaoyi Zhang, Fan Zhang, Lauren J. O'Donnell, Leo R. Zekelman, Nikos Makris, Steve Pieper, Suheyla Cetin-Karayumak, Tengfei Xue, Weidong Cai, William M. Wells, Yogesh Rathi, Yuqian Chen","submitted_at":"2022-10-13T23:24:12Z","abstract_excerpt":"Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely TractoSCR, that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography. TractoSCR performs supervised contrastive learning by using the absolute difference between continuous regression labels (i.e. neurocognitive scores) to determine positive and negative pairs. We app"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.07411","kind":"arxiv","version":2},"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/2210.07411/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":"2026-07-05T05:33:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u7Ok5h9BQc5zkCn4JfFtVRtbmP1sTObmg+15OUS+e6jqJnfFVt9DdV8PBIZIwWdtd/VBnPAMQK6/jQy6EYDbBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T05:27:38.752677Z"},"content_sha256":"a09131a374437883d997ba9bb1718fabe48b4b0726ff07894094f167fa06d6d9","schema_version":"1.0","event_id":"sha256:a09131a374437883d997ba9bb1718fabe48b4b0726ff07894094f167fa06d6d9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R6H5I4Z3NKZMO27KIULNZMGPUT/bundle.json","state_url":"https://pith.science/pith/R6H5I4Z3NKZMO27KIULNZMGPUT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R6H5I4Z3NKZMO27KIULNZMGPUT/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":"2026-08-15T05:27:38Z","links":{"resolver":"https://pith.science/pith/R6H5I4Z3NKZMO27KIULNZMGPUT","bundle":"https://pith.science/pith/R6H5I4Z3NKZMO27KIULNZMGPUT/bundle.json","state":"https://pith.science/pith/R6H5I4Z3NKZMO27KIULNZMGPUT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R6H5I4Z3NKZMO27KIULNZMGPUT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:R6H5I4Z3NKZMO27KIULNZMGPUT","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":"e3064fc9fe8063983b0b82c4a71c9db06a732913a6b6f22de77310e21f10c6cd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-13T23:24:12Z","title_canon_sha256":"cc4e610b21df43994dc7994dbcfce52270cd8cfff5272c6cce65f816f81bbf19"},"schema_version":"1.0","source":{"id":"2210.07411","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.07411","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"arxiv_version","alias_value":"2210.07411v2","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.07411","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"pith_short_12","alias_value":"R6H5I4Z3NKZM","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"pith_short_16","alias_value":"R6H5I4Z3NKZMO27K","created_at":"2026-07-05T05:33:19Z"},{"alias_kind":"pith_short_8","alias_value":"R6H5I4Z3","created_at":"2026-07-05T05:33:19Z"}],"graph_snapshots":[{"event_id":"sha256:a09131a374437883d997ba9bb1718fabe48b4b0726ff07894094f167fa06d6d9","target":"graph","created_at":"2026-07-05T05:33:19Z","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/2210.07411/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely TractoSCR, that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography. TractoSCR performs supervised contrastive learning by using the absolute difference between continuous regression labels (i.e. neurocognitive scores) to determine positive and negative pairs. We app","authors_text":"Chaoyi Zhang, Fan Zhang, Lauren J. O'Donnell, Leo R. Zekelman, Nikos Makris, Steve Pieper, Suheyla Cetin-Karayumak, Tengfei Xue, Weidong Cai, William M. Wells, Yogesh Rathi, Yuqian Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-13T23:24:12Z","title":"TractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.07411","kind":"arxiv","version":2},"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:f748bd93b8b37f37f193e2a08e77dc5f2ff0c794e7d8d59742b2f73f85a22501","target":"record","created_at":"2026-07-05T05:33:19Z","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":"e3064fc9fe8063983b0b82c4a71c9db06a732913a6b6f22de77310e21f10c6cd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-13T23:24:12Z","title_canon_sha256":"cc4e610b21df43994dc7994dbcfce52270cd8cfff5272c6cce65f816f81bbf19"},"schema_version":"1.0","source":{"id":"2210.07411","kind":"arxiv","version":2}},"canonical_sha256":"8f8fd4733b6ab2c76bea4516dcb0cfa4ca267c894e941507361057449ab6cf3c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8f8fd4733b6ab2c76bea4516dcb0cfa4ca267c894e941507361057449ab6cf3c","first_computed_at":"2026-07-05T05:33:19.441479Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:33:19.441479Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sd2dRAl6rDR6vEmfvM1tAD1XY2Tp05tfGpder+d/cF2jCYNH6OXinBgm9xCggOeePKE1y1VKztOfd4aj0FKDAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:33:19.441981Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.07411","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f748bd93b8b37f37f193e2a08e77dc5f2ff0c794e7d8d59742b2f73f85a22501","sha256:a09131a374437883d997ba9bb1718fabe48b4b0726ff07894094f167fa06d6d9"],"state_sha256":"33b3db7cea126769126dcfaa8840b69da78637f6217f1418d851f10af4c0054b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CREMXNwDtcV/tx6fHc/JVSd6/4bDGMKSWMjbwoEe6aiL5ZyofjqqzWmgV46zzkdwOidM5L2qjJ9HyCk57lXqBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T05:27:38.758114Z","bundle_sha256":"814336c4bd162c24a2cf8d106a7eb9bb75ebd1c6004fa0cd369cf37f52ab990d"}}