{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:IJIPVEG3EJG4JWM5GTWASXHKDP","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":"2caa404fdcac5d7ffa026e272b448c522ebaa3831ab2a8bd03e1fe3f98097f30","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-25T17:56:32Z","title_canon_sha256":"783188b688d877f102023dc891ba2d5bf74f3c70c3cc4af71511988633bda257"},"schema_version":"1.0","source":{"id":"1806.09602","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.09602","created_at":"2026-07-05T01:24:46Z"},{"alias_kind":"arxiv_version","alias_value":"1806.09602v2","created_at":"2026-07-05T01:24:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.09602","created_at":"2026-07-05T01:24:46Z"},{"alias_kind":"pith_short_12","alias_value":"IJIPVEG3EJG4","created_at":"2026-07-05T01:24:46Z"},{"alias_kind":"pith_short_16","alias_value":"IJIPVEG3EJG4JWM5","created_at":"2026-07-05T01:24:46Z"},{"alias_kind":"pith_short_8","alias_value":"IJIPVEG3","created_at":"2026-07-05T01:24:46Z"}],"graph_snapshots":[{"event_id":"sha256:58353aa63d8f53a2a4eb1230d42941a36d20829565b7d0c5cb5aa45c04c42db4","target":"graph","created_at":"2026-07-05T01:24:46Z","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/1806.09602/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and therefore time- and cost-intensive. Any imaging artifacts originating from scanner hardware, signal processing or induced by the patient may reduce the image quality and complicate the diagnosis or any image post-processing. Therefore, the assessment or the ensurance of sufficient image quality in an automated manner is of high interest. Usually no r","authors_text":"Annika Liebgott, Bin Yang, Fabian Bamberg, Fritz Schick, Holger Schmidt, Konstantin Nikolaou, Lukas Mauch, Martin Schwartz, Nina F. Schwenzer, Petros Martirosian, Sergios Gatidis, Thomas K\\\"ustner","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-25T17:56:32Z","title":"A Machine-learning framework for automatic reference-free quality assessment in MRI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.09602","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":"sha256:61529a2c82bf656beb9630c3e4ac279001815da2c3c1d6036c3a5a09099308bb","target":"record","created_at":"2026-07-05T01:24:46Z","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":"2caa404fdcac5d7ffa026e272b448c522ebaa3831ab2a8bd03e1fe3f98097f30","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-25T17:56:32Z","title_canon_sha256":"783188b688d877f102023dc891ba2d5bf74f3c70c3cc4af71511988633bda257"},"schema_version":"1.0","source":{"id":"1806.09602","kind":"arxiv","version":2}},"canonical_sha256":"4250fa90db224dc4d99d34ec095cea1bcd8fe45f7cda1c611c03d083af239867","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4250fa90db224dc4d99d34ec095cea1bcd8fe45f7cda1c611c03d083af239867","first_computed_at":"2026-07-05T01:24:46.482451Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:24:46.482451Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"siMtAZnvZc0JdlLp74pTt2G89G7snBs6q+z4If9nLHpg/YIXDWS94+wDHCVHS5NogifTRW9GgSw600Yjbb8CCA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:24:46.482906Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.09602","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:61529a2c82bf656beb9630c3e4ac279001815da2c3c1d6036c3a5a09099308bb","sha256:58353aa63d8f53a2a4eb1230d42941a36d20829565b7d0c5cb5aa45c04c42db4"],"state_sha256":"cf5daaf61e5b95bdb4581b99ae4b16ee802a5db786a302ea443c1ab2d41d309d"}