{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:NRMMENJZPDP6PNM4YWVO2O4HN6","short_pith_number":"pith:NRMMENJZ","canonical_record":{"source":{"id":"2507.13959","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T14:24:22Z","cross_cats_sorted":[],"title_canon_sha256":"0e461852a5e45bc64afac149efb064cab6d6f7dcb280546c83839699ffa817a8","abstract_canon_sha256":"9c46b35206e7558d63df012b7758a63a3ea9f9a2ea8b445dcab00b4deb0e8fc8"},"schema_version":"1.0"},"canonical_sha256":"6c58c2353978dfe7b59cc5aaed3b876f8eb5f4b901e445b95ee3d43228272d41","source":{"kind":"arxiv","id":"2507.13959","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.13959","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"arxiv_version","alias_value":"2507.13959v1","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.13959","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"pith_short_12","alias_value":"NRMMENJZPDP6","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"pith_short_16","alias_value":"NRMMENJZPDP6PNM4","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"pith_short_8","alias_value":"NRMMENJZ","created_at":"2026-07-05T11:39:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:NRMMENJZPDP6PNM4YWVO2O4HN6","target":"record","payload":{"canonical_record":{"source":{"id":"2507.13959","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T14:24:22Z","cross_cats_sorted":[],"title_canon_sha256":"0e461852a5e45bc64afac149efb064cab6d6f7dcb280546c83839699ffa817a8","abstract_canon_sha256":"9c46b35206e7558d63df012b7758a63a3ea9f9a2ea8b445dcab00b4deb0e8fc8"},"schema_version":"1.0"},"canonical_sha256":"6c58c2353978dfe7b59cc5aaed3b876f8eb5f4b901e445b95ee3d43228272d41","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:39:26.069808Z","signature_b64":"ZD7chTbsfKeEhCNjNVPYGIcuX7lbvdb4/XqfSm9MtJQRS7JoLTXU69B2xax8Jx5xMq5SA2EPok5FIwqPJi5uCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6c58c2353978dfe7b59cc5aaed3b876f8eb5f4b901e445b95ee3d43228272d41","last_reissued_at":"2026-07-05T11:39:26.069344Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:39:26.069344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.13959","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":"2026-07-05T11:39:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X84ETc3SwMot6exzrGzzP9rZVrGQHxLH51qzoeqOfxpm00u6j125v7Ab+003Sn3QGKwgbWb1yE4L1tZSsU7jDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T13:46:14.405798Z"},"content_sha256":"ecbf7a225a6d3352c2b3fae528113a85a7e347d03e6ad5be92def4d5ed39e5bf","schema_version":"1.0","event_id":"sha256:ecbf7a225a6d3352c2b3fae528113a85a7e347d03e6ad5be92def4d5ed39e5bf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:NRMMENJZPDP6PNM4YWVO2O4HN6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Signs of the Past, Patterns of the Present: On the Automatic Classification of Old Babylonian Cuneiform Signs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Eli Verwimp, Gustav Ryberg Smidt, Hendrik Hameeuw, Katrien De Graef","submitted_at":"2025-07-18T14:24:22Z","abstract_excerpt":"The work in this paper describes the training and evaluation of machine learning (ML) techniques for the classification of cuneiform signs. There is a lot of variability in cuneiform signs, depending on where they come from, for what and by whom they were written, but also how they were digitized. This variability makes it unlikely that an ML model trained on one dataset will perform successfully on another dataset. This contribution studies how such differences impact that performance. Based on our results and insights, we aim to influence future data acquisition standards and provide a solid"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.13959","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/2507.13959/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":"2026-07-05T11:39:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JP3+JqG0h4eG/jB7ytcomnFbuCFCE+oo1WNFMU/iGFCUUa60HGUbvw8esP2AOKNnqSkvtwkd+VvP94cM0UmSAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T13:46:14.406177Z"},"content_sha256":"6a6ace0b4ea298a52b24c8a5c0aaaafda3549240f4ceaf88810c5df5266b1255","schema_version":"1.0","event_id":"sha256:6a6ace0b4ea298a52b24c8a5c0aaaafda3549240f4ceaf88810c5df5266b1255"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NRMMENJZPDP6PNM4YWVO2O4HN6/bundle.json","state_url":"https://pith.science/pith/NRMMENJZPDP6PNM4YWVO2O4HN6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NRMMENJZPDP6PNM4YWVO2O4HN6/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":"2026-08-17T13:46:14Z","links":{"resolver":"https://pith.science/pith/NRMMENJZPDP6PNM4YWVO2O4HN6","bundle":"https://pith.science/pith/NRMMENJZPDP6PNM4YWVO2O4HN6/bundle.json","state":"https://pith.science/pith/NRMMENJZPDP6PNM4YWVO2O4HN6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NRMMENJZPDP6PNM4YWVO2O4HN6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:NRMMENJZPDP6PNM4YWVO2O4HN6","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":"9c46b35206e7558d63df012b7758a63a3ea9f9a2ea8b445dcab00b4deb0e8fc8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T14:24:22Z","title_canon_sha256":"0e461852a5e45bc64afac149efb064cab6d6f7dcb280546c83839699ffa817a8"},"schema_version":"1.0","source":{"id":"2507.13959","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.13959","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"arxiv_version","alias_value":"2507.13959v1","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.13959","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"pith_short_12","alias_value":"NRMMENJZPDP6","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"pith_short_16","alias_value":"NRMMENJZPDP6PNM4","created_at":"2026-07-05T11:39:26Z"},{"alias_kind":"pith_short_8","alias_value":"NRMMENJZ","created_at":"2026-07-05T11:39:26Z"}],"graph_snapshots":[{"event_id":"sha256:6a6ace0b4ea298a52b24c8a5c0aaaafda3549240f4ceaf88810c5df5266b1255","target":"graph","created_at":"2026-07-05T11:39:26Z","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/2507.13959/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The work in this paper describes the training and evaluation of machine learning (ML) techniques for the classification of cuneiform signs. There is a lot of variability in cuneiform signs, depending on where they come from, for what and by whom they were written, but also how they were digitized. This variability makes it unlikely that an ML model trained on one dataset will perform successfully on another dataset. This contribution studies how such differences impact that performance. Based on our results and insights, we aim to influence future data acquisition standards and provide a solid","authors_text":"Eli Verwimp, Gustav Ryberg Smidt, Hendrik Hameeuw, Katrien De Graef","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T14:24:22Z","title":"Signs of the Past, Patterns of the Present: On the Automatic Classification of Old Babylonian Cuneiform Signs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.13959","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:ecbf7a225a6d3352c2b3fae528113a85a7e347d03e6ad5be92def4d5ed39e5bf","target":"record","created_at":"2026-07-05T11:39:26Z","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":"9c46b35206e7558d63df012b7758a63a3ea9f9a2ea8b445dcab00b4deb0e8fc8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T14:24:22Z","title_canon_sha256":"0e461852a5e45bc64afac149efb064cab6d6f7dcb280546c83839699ffa817a8"},"schema_version":"1.0","source":{"id":"2507.13959","kind":"arxiv","version":1}},"canonical_sha256":"6c58c2353978dfe7b59cc5aaed3b876f8eb5f4b901e445b95ee3d43228272d41","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6c58c2353978dfe7b59cc5aaed3b876f8eb5f4b901e445b95ee3d43228272d41","first_computed_at":"2026-07-05T11:39:26.069344Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:39:26.069344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZD7chTbsfKeEhCNjNVPYGIcuX7lbvdb4/XqfSm9MtJQRS7JoLTXU69B2xax8Jx5xMq5SA2EPok5FIwqPJi5uCg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:39:26.069808Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.13959","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ecbf7a225a6d3352c2b3fae528113a85a7e347d03e6ad5be92def4d5ed39e5bf","sha256:6a6ace0b4ea298a52b24c8a5c0aaaafda3549240f4ceaf88810c5df5266b1255"],"state_sha256":"8f80fab5f0701a612545b136f11994cbb3f19e5b55d8988d537c5faf923c2e45"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6sSP36qZfYMQcUjvoUmScgPqzKL8yJNI1a6EgkbQwWjVmGtiPRHmMiDzu8RJnJJy3PlYecUFE36JB11nNovWCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T13:46:14.408724Z","bundle_sha256":"e3600c02352c4190fa82b31e7a96670d2b9da4f71a4169c0c85e89fb8a54a0c6"}}