{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:Y7KCR3YP4WNNPDN444TY3RQ4PM","short_pith_number":"pith:Y7KCR3YP","canonical_record":{"source":{"id":"2406.14325","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-06-20T13:56:42Z","cross_cats_sorted":["cs.IR","cs.LG"],"title_canon_sha256":"7c9edad4fc3919c31f8c9323311296b4a7053eda3785e34eafb0c3ff6fc570d1","abstract_canon_sha256":"9c4d91c1cbaa1836309c2a656147d6902f9ef1ce872dd5072ef78359bf473fae"},"schema_version":"1.0"},"canonical_sha256":"c7d428ef0fe59ad78dbce7278dc61c7b1be6b0493cc412ffae94df771fb7a804","source":{"kind":"arxiv","id":"2406.14325","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.14325","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"arxiv_version","alias_value":"2406.14325v3","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.14325","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"pith_short_12","alias_value":"Y7KCR3YP4WNN","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"pith_short_16","alias_value":"Y7KCR3YP4WNNPDN4","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"pith_short_8","alias_value":"Y7KCR3YP","created_at":"2026-07-05T10:20:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:Y7KCR3YP4WNNPDN444TY3RQ4PM","target":"record","payload":{"canonical_record":{"source":{"id":"2406.14325","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-06-20T13:56:42Z","cross_cats_sorted":["cs.IR","cs.LG"],"title_canon_sha256":"7c9edad4fc3919c31f8c9323311296b4a7053eda3785e34eafb0c3ff6fc570d1","abstract_canon_sha256":"9c4d91c1cbaa1836309c2a656147d6902f9ef1ce872dd5072ef78359bf473fae"},"schema_version":"1.0"},"canonical_sha256":"c7d428ef0fe59ad78dbce7278dc61c7b1be6b0493cc412ffae94df771fb7a804","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:20:12.981714Z","signature_b64":"1KQ4n7bSLMgBFyUZK/2dfqZlBzRW8RY7mmUktj6QelYssje3LPicbh3nWdlhPBJmmgc3bTLAivktXPZHENRNBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c7d428ef0fe59ad78dbce7278dc61c7b1be6b0493cc412ffae94df771fb7a804","last_reissued_at":"2026-07-05T10:20:12.981239Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:20:12.981239Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.14325","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:20:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o2sOmUstmLCe0M0LvECUjh/vprvAcppf0pxtURGoR1BN4AE85jt7CvILU3qhem8EA1ei9NpsrvYVrLw6BNO+Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T14:14:14.386284Z"},"content_sha256":"c1f20266329b16e559b3139763e4fb6b5e86aabb17ecdc8b4b6c11a9facd436e","schema_version":"1.0","event_id":"sha256:c1f20266329b16e559b3139763e4fb6b5e86aabb17ecdc8b4b6c11a9facd436e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:Y7KCR3YP4WNNPDN444TY3RQ4PM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR","cs.LG"],"primary_cat":"cs.SE","authors_text":"Armin Haberl, Dieter Theiler, Dominik Kowald, Harald Semmelrock, Simone Kopeinik, Stefan Thalmann, Tony Ross-Hellauer","submitted_at":"2024-06-20T13:56:42Z","abstract_excerpt":"Many research fields are currently reckoning with issues of poor levels of reproducibility. Some label it a \"crisis\", and research employing or building Machine Learning (ML) models is no exception. Issues including lack of transparency, data or code, poor adherence to standards, and the sensitivity of ML training conditions mean that many papers are not even reproducible in principle. Where they are, though, reproducibility experiments have found worryingly low degrees of similarity with original results. Despite previous appeals from ML researchers on this topic and various initiatives from "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.14325","kind":"arxiv","version":3},"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/2406.14325/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":"2026-07-05T10:20:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1WbiSCHhPoTlVWRolIE19vsEgZA/B4IoLFQaF1b/6zZv2so93CZH2ysqBUsv9U986ADw3R6HPB30BrccR6/VBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T14:14:14.386805Z"},"content_sha256":"b48c8ea50ac76302e2ca51946b8cbb3362e0b6af56108ff6e36351ccbf8096c7","schema_version":"1.0","event_id":"sha256:b48c8ea50ac76302e2ca51946b8cbb3362e0b6af56108ff6e36351ccbf8096c7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y7KCR3YP4WNNPDN444TY3RQ4PM/bundle.json","state_url":"https://pith.science/pith/Y7KCR3YP4WNNPDN444TY3RQ4PM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y7KCR3YP4WNNPDN444TY3RQ4PM/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":"2026-08-08T14:14:14Z","links":{"resolver":"https://pith.science/pith/Y7KCR3YP4WNNPDN444TY3RQ4PM","bundle":"https://pith.science/pith/Y7KCR3YP4WNNPDN444TY3RQ4PM/bundle.json","state":"https://pith.science/pith/Y7KCR3YP4WNNPDN444TY3RQ4PM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y7KCR3YP4WNNPDN444TY3RQ4PM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:Y7KCR3YP4WNNPDN444TY3RQ4PM","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":"9c4d91c1cbaa1836309c2a656147d6902f9ef1ce872dd5072ef78359bf473fae","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-06-20T13:56:42Z","title_canon_sha256":"7c9edad4fc3919c31f8c9323311296b4a7053eda3785e34eafb0c3ff6fc570d1"},"schema_version":"1.0","source":{"id":"2406.14325","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.14325","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"arxiv_version","alias_value":"2406.14325v3","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.14325","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"pith_short_12","alias_value":"Y7KCR3YP4WNN","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"pith_short_16","alias_value":"Y7KCR3YP4WNNPDN4","created_at":"2026-07-05T10:20:12Z"},{"alias_kind":"pith_short_8","alias_value":"Y7KCR3YP","created_at":"2026-07-05T10:20:12Z"}],"graph_snapshots":[{"event_id":"sha256:b48c8ea50ac76302e2ca51946b8cbb3362e0b6af56108ff6e36351ccbf8096c7","target":"graph","created_at":"2026-07-05T10:20:12Z","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/2406.14325/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many research fields are currently reckoning with issues of poor levels of reproducibility. Some label it a \"crisis\", and research employing or building Machine Learning (ML) models is no exception. Issues including lack of transparency, data or code, poor adherence to standards, and the sensitivity of ML training conditions mean that many papers are not even reproducible in principle. Where they are, though, reproducibility experiments have found worryingly low degrees of similarity with original results. Despite previous appeals from ML researchers on this topic and various initiatives from ","authors_text":"Armin Haberl, Dieter Theiler, Dominik Kowald, Harald Semmelrock, Simone Kopeinik, Stefan Thalmann, Tony Ross-Hellauer","cross_cats":["cs.IR","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-06-20T13:56:42Z","title":"Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.14325","kind":"arxiv","version":3},"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:c1f20266329b16e559b3139763e4fb6b5e86aabb17ecdc8b4b6c11a9facd436e","target":"record","created_at":"2026-07-05T10:20:12Z","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":"9c4d91c1cbaa1836309c2a656147d6902f9ef1ce872dd5072ef78359bf473fae","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-06-20T13:56:42Z","title_canon_sha256":"7c9edad4fc3919c31f8c9323311296b4a7053eda3785e34eafb0c3ff6fc570d1"},"schema_version":"1.0","source":{"id":"2406.14325","kind":"arxiv","version":3}},"canonical_sha256":"c7d428ef0fe59ad78dbce7278dc61c7b1be6b0493cc412ffae94df771fb7a804","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c7d428ef0fe59ad78dbce7278dc61c7b1be6b0493cc412ffae94df771fb7a804","first_computed_at":"2026-07-05T10:20:12.981239Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:20:12.981239Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1KQ4n7bSLMgBFyUZK/2dfqZlBzRW8RY7mmUktj6QelYssje3LPicbh3nWdlhPBJmmgc3bTLAivktXPZHENRNBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:20:12.981714Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.14325","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c1f20266329b16e559b3139763e4fb6b5e86aabb17ecdc8b4b6c11a9facd436e","sha256:b48c8ea50ac76302e2ca51946b8cbb3362e0b6af56108ff6e36351ccbf8096c7"],"state_sha256":"edf4c6493710fcff8dcd95d3c785526789584b1293c3965c2384db1953516566"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rLwH9EktppjgbM9g68uJbVCM8k6HE8i2oY3JUoE4YWSnp7QjUpIELOx3TkByxWiS/Ssfu2XdCYcN0orUrBrrAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T14:14:14.390574Z","bundle_sha256":"cbd0fde376aeac1c06400a76c04f3c28fcd621f103f70f512dea293bc7414cfe"}}