{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:LCKXXG4XZGHKDOQ2WPPGAMCA27","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":"7d9ec6eba6084b160515872d193e0ce69590347ba0aefaf4c996eec7e8b4d4f2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-12T02:45:32Z","title_canon_sha256":"58e687bedb77e2e7b780b765b396966809dbf6abb567d84e5900030f88d664c7"},"schema_version":"1.0","source":{"id":"1901.03786","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.03786","created_at":"2026-05-17T23:56:27Z"},{"alias_kind":"arxiv_version","alias_value":"1901.03786v1","created_at":"2026-05-17T23:56:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.03786","created_at":"2026-05-17T23:56:27Z"},{"alias_kind":"pith_short_12","alias_value":"LCKXXG4XZGHK","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"LCKXXG4XZGHKDOQ2","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"LCKXXG4X","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:0c4b55c1239e3bfd74d0783a1c3a777b2ed05266e7f6045ce5ed35fec67ca7b3","target":"graph","created_at":"2026-05-17T23:56:27Z","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"},"paper":{"abstract_excerpt":"Geologic interpretation of large seismic stacked or migrated seismic images can be a time-consuming task for seismic interpreters. Neural network based semantic segmentation provides fast and automatic interpretations, provided a sufficient number of example interpretations are available. Networks that map from image-to-image emerged recently as powerful tools for automatic segmentation, but standard implementations require fully interpreted examples. Generating training labels for large images manually is time consuming. We introduce a partial loss-function and labeling strategies such that n","authors_text":"Bas Peters, Eldad Haber, Justin Granek","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-12T02:45:32Z","title":"Automatic classification of geologic units in seismic images using partially interpreted examples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.03786","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:e4789908a8c9f23177e86439e3a179900a0720065c9cd93d1926908ad313ab09","target":"record","created_at":"2026-05-17T23:56:27Z","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":"7d9ec6eba6084b160515872d193e0ce69590347ba0aefaf4c996eec7e8b4d4f2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-12T02:45:32Z","title_canon_sha256":"58e687bedb77e2e7b780b765b396966809dbf6abb567d84e5900030f88d664c7"},"schema_version":"1.0","source":{"id":"1901.03786","kind":"arxiv","version":1}},"canonical_sha256":"58957b9b97c98ea1ba1ab3de603040d7e92a595435e2e4a6ccc79501a64d567e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"58957b9b97c98ea1ba1ab3de603040d7e92a595435e2e4a6ccc79501a64d567e","first_computed_at":"2026-05-17T23:56:27.062125Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:27.062125Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MaRodRdhtO4Dqvz5apVKKl5yOJrzXMc414oHhdu9pe/qz6lruMs0nv0KdMgiLwpGJCMTGqnGPRrcw/Q9uiL2CA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:27.062632Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.03786","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4789908a8c9f23177e86439e3a179900a0720065c9cd93d1926908ad313ab09","sha256:0c4b55c1239e3bfd74d0783a1c3a777b2ed05266e7f6045ce5ed35fec67ca7b3"],"state_sha256":"eef472c1e36ede10fb27d72d41c4be105f6cd4c70d03f4181deae30d1d6359ba"}