{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:RYLGGMHZY4CWDSX3RYNOVZWFG6","short_pith_number":"pith:RYLGGMHZ","canonical_record":{"source":{"id":"2607.06356","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-07T14:54:40Z","cross_cats_sorted":[],"title_canon_sha256":"28ae9d1b37c0bcb9564e30606db58495f621220301c923a93a23e1a75b8a779e","abstract_canon_sha256":"ab67c73253df0fddfd0a0a9ed94ed2ea703d0f75acde2ade00eaf2f1bbba43cf"},"schema_version":"1.0"},"canonical_sha256":"8e166330f9c70561cafb8e1aeae6c537b8bdfd922b928259dba0a1db73a1a91e","source":{"kind":"arxiv","id":"2607.06356","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.06356","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"arxiv_version","alias_value":"2607.06356v1","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06356","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"pith_short_12","alias_value":"RYLGGMHZY4CW","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"pith_short_16","alias_value":"RYLGGMHZY4CWDSX3","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"pith_short_8","alias_value":"RYLGGMHZ","created_at":"2026-07-08T01:19:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:RYLGGMHZY4CWDSX3RYNOVZWFG6","target":"record","payload":{"canonical_record":{"source":{"id":"2607.06356","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-07T14:54:40Z","cross_cats_sorted":[],"title_canon_sha256":"28ae9d1b37c0bcb9564e30606db58495f621220301c923a93a23e1a75b8a779e","abstract_canon_sha256":"ab67c73253df0fddfd0a0a9ed94ed2ea703d0f75acde2ade00eaf2f1bbba43cf"},"schema_version":"1.0"},"canonical_sha256":"8e166330f9c70561cafb8e1aeae6c537b8bdfd922b928259dba0a1db73a1a91e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-08T01:19:23.242749Z","signature_b64":"jG5RE1NEekQDO9smQOJW4xin0n/pxPCfU1ykrZKYfUJgyadHNkP+zou6bVFJZe+XAv91bVSaauCVDemSPrXpAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e166330f9c70561cafb8e1aeae6c537b8bdfd922b928259dba0a1db73a1a91e","last_reissued_at":"2026-07-08T01:19:23.242328Z","signature_status":"signed_v1","first_computed_at":"2026-07-08T01:19:23.242328Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.06356","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":"2026-07-08T01:19:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JU7LMvXJg1D5ee0LF3tasvqSIt0cJdAX9i9rkMONNnreKGvj9IPk7IGNYYlG1wzNGif30x3gq/3JhPMTFw9ZCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T22:22:35.364451Z"},"content_sha256":"e4964bacff7d5a3353de5a281b1c6340eeb119a9b31ae2fc8142de0c66c62303","schema_version":"1.0","event_id":"sha256:e4964bacff7d5a3353de5a281b1c6340eeb119a9b31ae2fc8142de0c66c62303"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:RYLGGMHZY4CWDSX3RYNOVZWFG6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TMF-RSE: Tri-Modal Fusion with Regional Semantics and Evidential Uncertainty for Lung Severity Scoring","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abdellah Zakaria Sellam, Cosimo Distante, Fadi Abdeladhim Zidi, Fadi Dornaika, Gaby Maroun, Salah Eddine Bekhouche","submitted_at":"2026-07-07T14:54:40Z","abstract_excerpt":"Accurate quantification of lung disease severity from chest imaging is critical for clinical decision-making and resource allocation. We propose a tri-modal deep learning framework, TMF-RSE (Tri-Modal Fusion with Regional Semantics and Evidential Uncertainty), that combines appearance features from two-dimensional chest inputs, structural features from lung segmentation masks, and semantic features from vision-language models (VLMs) for severity quantification. Our approach employs complementary fusion mechanisms that integrate semantic guidance, structural priors, and hierarchical interaction"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06356","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/2607.06356/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":"2026-07-08T01:19:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nY0Pd3N+g3nXeOiLn1PmhDexpQ5CQfGLoNoriARNpW4uP+vZnvBSACF9oc/cA7otzvxJ08jFxp+dl9wr31EtAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T22:22:35.365118Z"},"content_sha256":"86f32efb890bb3785a4f703bb6a32d8f81531bcc375a1a27ea31df86aeffdcb8","schema_version":"1.0","event_id":"sha256:86f32efb890bb3785a4f703bb6a32d8f81531bcc375a1a27ea31df86aeffdcb8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RYLGGMHZY4CWDSX3RYNOVZWFG6/bundle.json","state_url":"https://pith.science/pith/RYLGGMHZY4CWDSX3RYNOVZWFG6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RYLGGMHZY4CWDSX3RYNOVZWFG6/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":"2026-08-20T22:22:35Z","links":{"resolver":"https://pith.science/pith/RYLGGMHZY4CWDSX3RYNOVZWFG6","bundle":"https://pith.science/pith/RYLGGMHZY4CWDSX3RYNOVZWFG6/bundle.json","state":"https://pith.science/pith/RYLGGMHZY4CWDSX3RYNOVZWFG6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RYLGGMHZY4CWDSX3RYNOVZWFG6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:RYLGGMHZY4CWDSX3RYNOVZWFG6","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":"ab67c73253df0fddfd0a0a9ed94ed2ea703d0f75acde2ade00eaf2f1bbba43cf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-07T14:54:40Z","title_canon_sha256":"28ae9d1b37c0bcb9564e30606db58495f621220301c923a93a23e1a75b8a779e"},"schema_version":"1.0","source":{"id":"2607.06356","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.06356","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"arxiv_version","alias_value":"2607.06356v1","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06356","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"pith_short_12","alias_value":"RYLGGMHZY4CW","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"pith_short_16","alias_value":"RYLGGMHZY4CWDSX3","created_at":"2026-07-08T01:19:23Z"},{"alias_kind":"pith_short_8","alias_value":"RYLGGMHZ","created_at":"2026-07-08T01:19:23Z"}],"graph_snapshots":[{"event_id":"sha256:86f32efb890bb3785a4f703bb6a32d8f81531bcc375a1a27ea31df86aeffdcb8","target":"graph","created_at":"2026-07-08T01:19:23Z","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/2607.06356/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate quantification of lung disease severity from chest imaging is critical for clinical decision-making and resource allocation. We propose a tri-modal deep learning framework, TMF-RSE (Tri-Modal Fusion with Regional Semantics and Evidential Uncertainty), that combines appearance features from two-dimensional chest inputs, structural features from lung segmentation masks, and semantic features from vision-language models (VLMs) for severity quantification. Our approach employs complementary fusion mechanisms that integrate semantic guidance, structural priors, and hierarchical interaction","authors_text":"Abdellah Zakaria Sellam, Cosimo Distante, Fadi Abdeladhim Zidi, Fadi Dornaika, Gaby Maroun, Salah Eddine Bekhouche","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-07T14:54:40Z","title":"TMF-RSE: Tri-Modal Fusion with Regional Semantics and Evidential Uncertainty for Lung Severity Scoring"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06356","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:e4964bacff7d5a3353de5a281b1c6340eeb119a9b31ae2fc8142de0c66c62303","target":"record","created_at":"2026-07-08T01:19:23Z","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":"ab67c73253df0fddfd0a0a9ed94ed2ea703d0f75acde2ade00eaf2f1bbba43cf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-07T14:54:40Z","title_canon_sha256":"28ae9d1b37c0bcb9564e30606db58495f621220301c923a93a23e1a75b8a779e"},"schema_version":"1.0","source":{"id":"2607.06356","kind":"arxiv","version":1}},"canonical_sha256":"8e166330f9c70561cafb8e1aeae6c537b8bdfd922b928259dba0a1db73a1a91e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e166330f9c70561cafb8e1aeae6c537b8bdfd922b928259dba0a1db73a1a91e","first_computed_at":"2026-07-08T01:19:23.242328Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-08T01:19:23.242328Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jG5RE1NEekQDO9smQOJW4xin0n/pxPCfU1ykrZKYfUJgyadHNkP+zou6bVFJZe+XAv91bVSaauCVDemSPrXpAQ==","signature_status":"signed_v1","signed_at":"2026-07-08T01:19:23.242749Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.06356","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4964bacff7d5a3353de5a281b1c6340eeb119a9b31ae2fc8142de0c66c62303","sha256:86f32efb890bb3785a4f703bb6a32d8f81531bcc375a1a27ea31df86aeffdcb8"],"state_sha256":"a7b4f928fa24fb30c18e0ff4aa96f33e30cc58dc68b94f39e46c435c4b4e2a3b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ap1gQKdBQEMiGaOcO5qUspl1+qC3rA57Z/o2j7JGPeFZR8zze7V954NOy+4qNQ2t0AUIAs+6seDXmqm6wauECg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T22:22:35.371015Z","bundle_sha256":"02550595937e444733e4d01adcfb38f2c0f3f72a0bc89171a0c0cbf0e119f0bf"}}