{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:YK4R2P3X6E4S4Z6PNF7NJDLWHL","short_pith_number":"pith:YK4R2P3X","canonical_record":{"source":{"id":"1805.00329","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-23T20:00:42Z","cross_cats_sorted":[],"title_canon_sha256":"d658e1253e60a678aafad18b70983eea76d766e140c1341cca18299ff76a3280","abstract_canon_sha256":"a70d8a7e60121bbabf5357f3f484ad80b20bff5c5c6079411eccdeaefb90d1b1"},"schema_version":"1.0"},"canonical_sha256":"c2b91d3f77f1392e67cf697ed48d763ad7a246849096c99058c7d77c89bd8ced","source":{"kind":"arxiv","id":"1805.00329","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.00329","created_at":"2026-05-18T00:17:09Z"},{"alias_kind":"arxiv_version","alias_value":"1805.00329v1","created_at":"2026-05-18T00:17:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.00329","created_at":"2026-05-18T00:17:09Z"},{"alias_kind":"pith_short_12","alias_value":"YK4R2P3X6E4S","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YK4R2P3X6E4S4Z6P","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YK4R2P3X","created_at":"2026-05-18T12:33:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:YK4R2P3X6E4S4Z6PNF7NJDLWHL","target":"record","payload":{"canonical_record":{"source":{"id":"1805.00329","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-23T20:00:42Z","cross_cats_sorted":[],"title_canon_sha256":"d658e1253e60a678aafad18b70983eea76d766e140c1341cca18299ff76a3280","abstract_canon_sha256":"a70d8a7e60121bbabf5357f3f484ad80b20bff5c5c6079411eccdeaefb90d1b1"},"schema_version":"1.0"},"canonical_sha256":"c2b91d3f77f1392e67cf697ed48d763ad7a246849096c99058c7d77c89bd8ced","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:17:09.887707Z","signature_b64":"EbkpQJ/jCaqUBBZ8X3rW5lNjwsmJD0ANkhveI43o6tuOP+gSPDIb0Ej4KKlUSraXnqhyBTE+IwUsF6GdjHw7Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2b91d3f77f1392e67cf697ed48d763ad7a246849096c99058c7d77c89bd8ced","last_reissued_at":"2026-05-18T00:17:09.887162Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:17:09.887162Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.00329","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":"2026-05-18T00:17:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P0pMqMueCunfaNJ01WAlQm4P2bF4lMOpT3OaAHtxAO5zQEp08ytlIzVBX3lDyPbAF0xZ/wqzfAHR+BweQlzODg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:37:55.987678Z"},"content_sha256":"d66a4e86653aee5b1c5922fe1740e2b3ed2ca24e5a680e402ed88fbadec86408","schema_version":"1.0","event_id":"sha256:d66a4e86653aee5b1c5922fe1740e2b3ed2ca24e5a680e402ed88fbadec86408"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:YK4R2P3X6E4S4Z6PNF7NJDLWHL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Marcel W\\\"ursch, Marcus Liwicki, Michele Alberti, Rolf Ingold, Vinaychandran Pondenkandath","submitted_at":"2018-04-23T20:00:42Z","abstract_excerpt":"We introduce DeepDIVA: an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing scientific results can be a frustrating experience, not only in document image analysis but in machine learning in general. Using DeepDIVA a researcher can either reproduce a given experiment with a very limited amount of information or share their own experiments with others. Moreover, the framework offers a large range of functions, such as boilerplate code, keeping track of experiments, hyper-parameter optimization"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.00329","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":""},"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":"2026-05-18T00:17:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/+SPXRdf9HoPa5B28tMsJzYbOOx3lTIMzzEfg8BDMlosOFte+fDAM2kigQjstXDUbojK5ggrkd73ij0FBFg6DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:37:55.988038Z"},"content_sha256":"147fe6f11677d3f34e0d5a3d1ff36ef7b311a16e6af2ee64e4dd446deefd4114","schema_version":"1.0","event_id":"sha256:147fe6f11677d3f34e0d5a3d1ff36ef7b311a16e6af2ee64e4dd446deefd4114"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YK4R2P3X6E4S4Z6PNF7NJDLWHL/bundle.json","state_url":"https://pith.science/pith/YK4R2P3X6E4S4Z6PNF7NJDLWHL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YK4R2P3X6E4S4Z6PNF7NJDLWHL/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":"2026-06-02T14:37:55Z","links":{"resolver":"https://pith.science/pith/YK4R2P3X6E4S4Z6PNF7NJDLWHL","bundle":"https://pith.science/pith/YK4R2P3X6E4S4Z6PNF7NJDLWHL/bundle.json","state":"https://pith.science/pith/YK4R2P3X6E4S4Z6PNF7NJDLWHL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YK4R2P3X6E4S4Z6PNF7NJDLWHL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:YK4R2P3X6E4S4Z6PNF7NJDLWHL","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":"a70d8a7e60121bbabf5357f3f484ad80b20bff5c5c6079411eccdeaefb90d1b1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-23T20:00:42Z","title_canon_sha256":"d658e1253e60a678aafad18b70983eea76d766e140c1341cca18299ff76a3280"},"schema_version":"1.0","source":{"id":"1805.00329","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.00329","created_at":"2026-05-18T00:17:09Z"},{"alias_kind":"arxiv_version","alias_value":"1805.00329v1","created_at":"2026-05-18T00:17:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.00329","created_at":"2026-05-18T00:17:09Z"},{"alias_kind":"pith_short_12","alias_value":"YK4R2P3X6E4S","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YK4R2P3X6E4S4Z6P","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YK4R2P3X","created_at":"2026-05-18T12:33:04Z"}],"graph_snapshots":[{"event_id":"sha256:147fe6f11677d3f34e0d5a3d1ff36ef7b311a16e6af2ee64e4dd446deefd4114","target":"graph","created_at":"2026-05-18T00:17:09Z","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":"We introduce DeepDIVA: an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing scientific results can be a frustrating experience, not only in document image analysis but in machine learning in general. Using DeepDIVA a researcher can either reproduce a given experiment with a very limited amount of information or share their own experiments with others. Moreover, the framework offers a large range of functions, such as boilerplate code, keeping track of experiments, hyper-parameter optimization","authors_text":"Marcel W\\\"ursch, Marcus Liwicki, Michele Alberti, Rolf Ingold, Vinaychandran Pondenkandath","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-23T20:00:42Z","title":"DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.00329","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:d66a4e86653aee5b1c5922fe1740e2b3ed2ca24e5a680e402ed88fbadec86408","target":"record","created_at":"2026-05-18T00:17:09Z","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":"a70d8a7e60121bbabf5357f3f484ad80b20bff5c5c6079411eccdeaefb90d1b1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-23T20:00:42Z","title_canon_sha256":"d658e1253e60a678aafad18b70983eea76d766e140c1341cca18299ff76a3280"},"schema_version":"1.0","source":{"id":"1805.00329","kind":"arxiv","version":1}},"canonical_sha256":"c2b91d3f77f1392e67cf697ed48d763ad7a246849096c99058c7d77c89bd8ced","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c2b91d3f77f1392e67cf697ed48d763ad7a246849096c99058c7d77c89bd8ced","first_computed_at":"2026-05-18T00:17:09.887162Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:17:09.887162Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EbkpQJ/jCaqUBBZ8X3rW5lNjwsmJD0ANkhveI43o6tuOP+gSPDIb0Ej4KKlUSraXnqhyBTE+IwUsF6GdjHw7Dw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:17:09.887707Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.00329","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d66a4e86653aee5b1c5922fe1740e2b3ed2ca24e5a680e402ed88fbadec86408","sha256:147fe6f11677d3f34e0d5a3d1ff36ef7b311a16e6af2ee64e4dd446deefd4114"],"state_sha256":"64c8a9ee92df2bc023b11287a82d46f20c81079e02146e81aba0ec0d25b86c87"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iEMHEUS82t7VZUic38ninCX1RgVWGIyrT/5HThCKC8AtBi0icGXGyz6GQ4Vt48XkjM1OKOoHK60kY9wIpAynDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T14:37:55.990071Z","bundle_sha256":"6e605abfc7b0c90282ba3b59cc0b58ba4882be4b9606bcde0ec3a66011a96400"}}