{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WMXRQRTVCSNKHDOYTDEPVQRYAE","short_pith_number":"pith:WMXRQRTV","canonical_record":{"source":{"id":"2607.09916","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T19:07:48Z","cross_cats_sorted":[],"title_canon_sha256":"056887334358281da6cb864f288c60b7b43d6bb5e75843c274144e66b5e88afb","abstract_canon_sha256":"62f6eccd728c4a69b4c99938d4ce9aa8593fabc6b1e3cf00ec3b8dab39348808"},"schema_version":"1.0"},"canonical_sha256":"b32f184675149aa38dd898c8fac238012db6c1d2b6ffe02476374d5a800c0b52","source":{"kind":"arxiv","id":"2607.09916","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.09916","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"arxiv_version","alias_value":"2607.09916v1","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.09916","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"pith_short_12","alias_value":"WMXRQRTVCSNK","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"pith_short_16","alias_value":"WMXRQRTVCSNKHDOY","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"pith_short_8","alias_value":"WMXRQRTV","created_at":"2026-07-14T00:18:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WMXRQRTVCSNKHDOYTDEPVQRYAE","target":"record","payload":{"canonical_record":{"source":{"id":"2607.09916","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T19:07:48Z","cross_cats_sorted":[],"title_canon_sha256":"056887334358281da6cb864f288c60b7b43d6bb5e75843c274144e66b5e88afb","abstract_canon_sha256":"62f6eccd728c4a69b4c99938d4ce9aa8593fabc6b1e3cf00ec3b8dab39348808"},"schema_version":"1.0"},"canonical_sha256":"b32f184675149aa38dd898c8fac238012db6c1d2b6ffe02476374d5a800c0b52","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-14T00:18:42.861204Z","signature_b64":"Vd0h+MM5rKHrUse1x0vUcm5YaKNFKst+1z4DA7j7ob0qIL+1ANqWKtagz72VrWMZO+zbKagoPoYMSVQMrdLvDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b32f184675149aa38dd898c8fac238012db6c1d2b6ffe02476374d5a800c0b52","last_reissued_at":"2026-07-14T00:18:42.860364Z","signature_status":"signed_v1","first_computed_at":"2026-07-14T00:18:42.860364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.09916","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":"2026-07-14T00:18:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"takL8rOkJN0S3rfXxHBwPuTmwF9q8ISlRhCdHRXY6RwNle+gWo7XiK2qRvQ2lfmY7CTZ+P7xmvE1AzB34c88BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T15:18:03.356529Z"},"content_sha256":"75fb3ec74d011e0648db927cf540d80c367de2bde1977d7641248d88385e6e68","schema_version":"1.0","event_id":"sha256:75fb3ec74d011e0648db927cf540d80c367de2bde1977d7641248d88385e6e68"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WMXRQRTVCSNKHDOYTDEPVQRYAE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tomo-center: an AI-based rotation-axis center finder for synchrotron micro- and nano-tomography","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Alberto Mittone, Francesco De Carlo, Samuel J. Clark, Songyuan Tang, Viktor Nikitin, Xiaoyang Liu","submitted_at":"2026-07-10T19:07:48Z","abstract_excerpt":"Accurate determination of the rotation-axis position is a prerequisite for artifact-free reconstruction in parallel-beam synchrotron micro-tomography. Traditional approaches such as Vo's method rely on sinogram features that can fail for low-contrast or weakly absorbing specimens. We present a learning-based method that treats center selection as a binary classification problem, using a DINOv2-pretrained vision transformer aggregated with attention-based multiple-instance learning, fine-tuned end-to-end on tomographic images. At inference time, the proposed algorithm was applied to a stack of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.09916","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/2607.09916/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":"2026-07-14T00:18:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rt6s4xdduaRL5syJBmjKdAtz6vNGmJ7V5daZYZtbU3+mGXyDZLTpWMvrejQeb1dL8owN2PaFVX2Jc+fEBfMxCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T15:18:03.357012Z"},"content_sha256":"c9c47786aadfdf1b52a9121668a847444c7d775abc22d7e4c7e67454ef1da4da","schema_version":"1.0","event_id":"sha256:c9c47786aadfdf1b52a9121668a847444c7d775abc22d7e4c7e67454ef1da4da"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WMXRQRTVCSNKHDOYTDEPVQRYAE/bundle.json","state_url":"https://pith.science/pith/WMXRQRTVCSNKHDOYTDEPVQRYAE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WMXRQRTVCSNKHDOYTDEPVQRYAE/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":"2026-08-07T15:18:03Z","links":{"resolver":"https://pith.science/pith/WMXRQRTVCSNKHDOYTDEPVQRYAE","bundle":"https://pith.science/pith/WMXRQRTVCSNKHDOYTDEPVQRYAE/bundle.json","state":"https://pith.science/pith/WMXRQRTVCSNKHDOYTDEPVQRYAE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WMXRQRTVCSNKHDOYTDEPVQRYAE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WMXRQRTVCSNKHDOYTDEPVQRYAE","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":"62f6eccd728c4a69b4c99938d4ce9aa8593fabc6b1e3cf00ec3b8dab39348808","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T19:07:48Z","title_canon_sha256":"056887334358281da6cb864f288c60b7b43d6bb5e75843c274144e66b5e88afb"},"schema_version":"1.0","source":{"id":"2607.09916","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.09916","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"arxiv_version","alias_value":"2607.09916v1","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.09916","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"pith_short_12","alias_value":"WMXRQRTVCSNK","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"pith_short_16","alias_value":"WMXRQRTVCSNKHDOY","created_at":"2026-07-14T00:18:42Z"},{"alias_kind":"pith_short_8","alias_value":"WMXRQRTV","created_at":"2026-07-14T00:18:42Z"}],"graph_snapshots":[{"event_id":"sha256:c9c47786aadfdf1b52a9121668a847444c7d775abc22d7e4c7e67454ef1da4da","target":"graph","created_at":"2026-07-14T00:18:42Z","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/2607.09916/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate determination of the rotation-axis position is a prerequisite for artifact-free reconstruction in parallel-beam synchrotron micro-tomography. Traditional approaches such as Vo's method rely on sinogram features that can fail for low-contrast or weakly absorbing specimens. We present a learning-based method that treats center selection as a binary classification problem, using a DINOv2-pretrained vision transformer aggregated with attention-based multiple-instance learning, fine-tuned end-to-end on tomographic images. At inference time, the proposed algorithm was applied to a stack of ","authors_text":"Alberto Mittone, Francesco De Carlo, Samuel J. Clark, Songyuan Tang, Viktor Nikitin, Xiaoyang Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T19:07:48Z","title":"Tomo-center: an AI-based rotation-axis center finder for synchrotron micro- and nano-tomography"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.09916","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":"sha256:75fb3ec74d011e0648db927cf540d80c367de2bde1977d7641248d88385e6e68","target":"record","created_at":"2026-07-14T00:18:42Z","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":"62f6eccd728c4a69b4c99938d4ce9aa8593fabc6b1e3cf00ec3b8dab39348808","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T19:07:48Z","title_canon_sha256":"056887334358281da6cb864f288c60b7b43d6bb5e75843c274144e66b5e88afb"},"schema_version":"1.0","source":{"id":"2607.09916","kind":"arxiv","version":1}},"canonical_sha256":"b32f184675149aa38dd898c8fac238012db6c1d2b6ffe02476374d5a800c0b52","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b32f184675149aa38dd898c8fac238012db6c1d2b6ffe02476374d5a800c0b52","first_computed_at":"2026-07-14T00:18:42.860364Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T00:18:42.860364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Vd0h+MM5rKHrUse1x0vUcm5YaKNFKst+1z4DA7j7ob0qIL+1ANqWKtagz72VrWMZO+zbKagoPoYMSVQMrdLvDA==","signature_status":"signed_v1","signed_at":"2026-07-14T00:18:42.861204Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.09916","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75fb3ec74d011e0648db927cf540d80c367de2bde1977d7641248d88385e6e68","sha256:c9c47786aadfdf1b52a9121668a847444c7d775abc22d7e4c7e67454ef1da4da"],"state_sha256":"380fd02336b670129deeef9174ca4f8b9863b0bf94dfce0f7edb0119f231b2b4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eQpR/ZHdo1ckZIZl9Go6v+Xr3hjqf3Pn+gCgXWZUQlxYxQWzyZdLqhOYfSooojhrDAN1abIu5xiG2ofOR0i5Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T15:18:03.361175Z","bundle_sha256":"f0486a1945f819a285ff13d36f32493fd1cedd12576a63fb1aa72ffaae71e7e0"}}