{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:HWXFPFVKJ3Q2QPBKVRREVON2E4","short_pith_number":"pith:HWXFPFVK","canonical_record":{"source":{"id":"2402.12867","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.SE","submitted_at":"2024-02-20T09:57:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"bdd181b89b87bb587343757f4a157245df22615dfca9cd68e09fe51255efb9c1","abstract_canon_sha256":"cbef10c78f802df2df00dc7321ab283cd8411435197325b11bf6ac4cd14ed087"},"schema_version":"1.0"},"canonical_sha256":"3dae5796aa4ee1a83c2aac624ab9ba271e1c81267f401dd88b510bd2164a3b54","source":{"kind":"arxiv","id":"2402.12867","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.12867","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"arxiv_version","alias_value":"2402.12867v1","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.12867","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"pith_short_12","alias_value":"HWXFPFVKJ3Q2","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"pith_short_16","alias_value":"HWXFPFVKJ3Q2QPBK","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"pith_short_8","alias_value":"HWXFPFVK","created_at":"2026-07-05T07:47:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:HWXFPFVKJ3Q2QPBKVRREVON2E4","target":"record","payload":{"canonical_record":{"source":{"id":"2402.12867","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.SE","submitted_at":"2024-02-20T09:57:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"bdd181b89b87bb587343757f4a157245df22615dfca9cd68e09fe51255efb9c1","abstract_canon_sha256":"cbef10c78f802df2df00dc7321ab283cd8411435197325b11bf6ac4cd14ed087"},"schema_version":"1.0"},"canonical_sha256":"3dae5796aa4ee1a83c2aac624ab9ba271e1c81267f401dd88b510bd2164a3b54","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:47:17.560644Z","signature_b64":"He8ShKyIiSxOGGr1hfiemuzOfhBjXAS+fvk2wkczOlRemCFmXMEcjSn2VlmhSdupdBIFIChbuNaissv2y4zGCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3dae5796aa4ee1a83c2aac624ab9ba271e1c81267f401dd88b510bd2164a3b54","last_reissued_at":"2026-07-05T07:47:17.560183Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:47:17.560183Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.12867","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":"2026-07-05T07:47:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D2PQ3jDrF9LveDA5tC0KRACccxUJIM3sdPCKLt1/AqlYKoaD5OegGqbOTnqoDssCFnTXVJ2gPi4aShjJ6Sf3AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T13:08:48.523845Z"},"content_sha256":"56c9e3ca582f4c9e20a59fcb51d3301124fa6353b7af91cd3d5e1a694aeb4751","schema_version":"1.0","event_id":"sha256:56c9e3ca582f4c9e20a59fcb51d3301124fa6353b7af91cd3d5e1a694aeb4751"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:HWXFPFVKJ3Q2QPBKVRREVON2E4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards MLOps: A DevOps Tools Recommender System for Machine Learning System","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SE","authors_text":"Mirza Omer Beg, Naveed Ahmad, Pir Sami Ullah Shah","submitted_at":"2024-02-20T09:57:49Z","abstract_excerpt":"Applying DevOps practices to machine learning system is termed as MLOps and machine learning systems evolve on new data unlike traditional systems on requirements. The objective of MLOps is to establish a connection between different open-source tools to construct a pipeline that can automatically perform steps to construct a dataset, train the machine learning model and deploy the model to the production as well as store different versions of model and dataset. Benefits of MLOps is to make sure the fast delivery of the new trained models to the production to have accurate results. Furthermore"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.12867","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/2402.12867/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":"2026-07-05T07:47:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WhXcgskYCGiEGHmU2gYL6mCGStux/wNxEQtwErRJWKrWz/TTythZc0l1IJIDnFzqbTclaBiP9N1mOgLPkWOsCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T13:08:48.524357Z"},"content_sha256":"18af4be180a9d1f632983cae4cd1302b4e031c59acaebb0a3b91451fb46496d0","schema_version":"1.0","event_id":"sha256:18af4be180a9d1f632983cae4cd1302b4e031c59acaebb0a3b91451fb46496d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HWXFPFVKJ3Q2QPBKVRREVON2E4/bundle.json","state_url":"https://pith.science/pith/HWXFPFVKJ3Q2QPBKVRREVON2E4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HWXFPFVKJ3Q2QPBKVRREVON2E4/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":"2026-08-16T13:08:48Z","links":{"resolver":"https://pith.science/pith/HWXFPFVKJ3Q2QPBKVRREVON2E4","bundle":"https://pith.science/pith/HWXFPFVKJ3Q2QPBKVRREVON2E4/bundle.json","state":"https://pith.science/pith/HWXFPFVKJ3Q2QPBKVRREVON2E4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HWXFPFVKJ3Q2QPBKVRREVON2E4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HWXFPFVKJ3Q2QPBKVRREVON2E4","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":"cbef10c78f802df2df00dc7321ab283cd8411435197325b11bf6ac4cd14ed087","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.SE","submitted_at":"2024-02-20T09:57:49Z","title_canon_sha256":"bdd181b89b87bb587343757f4a157245df22615dfca9cd68e09fe51255efb9c1"},"schema_version":"1.0","source":{"id":"2402.12867","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.12867","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"arxiv_version","alias_value":"2402.12867v1","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.12867","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"pith_short_12","alias_value":"HWXFPFVKJ3Q2","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"pith_short_16","alias_value":"HWXFPFVKJ3Q2QPBK","created_at":"2026-07-05T07:47:17Z"},{"alias_kind":"pith_short_8","alias_value":"HWXFPFVK","created_at":"2026-07-05T07:47:17Z"}],"graph_snapshots":[{"event_id":"sha256:18af4be180a9d1f632983cae4cd1302b4e031c59acaebb0a3b91451fb46496d0","target":"graph","created_at":"2026-07-05T07:47:17Z","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/2402.12867/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Applying DevOps practices to machine learning system is termed as MLOps and machine learning systems evolve on new data unlike traditional systems on requirements. The objective of MLOps is to establish a connection between different open-source tools to construct a pipeline that can automatically perform steps to construct a dataset, train the machine learning model and deploy the model to the production as well as store different versions of model and dataset. Benefits of MLOps is to make sure the fast delivery of the new trained models to the production to have accurate results. Furthermore","authors_text":"Mirza Omer Beg, Naveed Ahmad, Pir Sami Ullah Shah","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.SE","submitted_at":"2024-02-20T09:57:49Z","title":"Towards MLOps: A DevOps Tools Recommender System for Machine Learning System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.12867","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":"sha256:56c9e3ca582f4c9e20a59fcb51d3301124fa6353b7af91cd3d5e1a694aeb4751","target":"record","created_at":"2026-07-05T07:47:17Z","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":"cbef10c78f802df2df00dc7321ab283cd8411435197325b11bf6ac4cd14ed087","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.SE","submitted_at":"2024-02-20T09:57:49Z","title_canon_sha256":"bdd181b89b87bb587343757f4a157245df22615dfca9cd68e09fe51255efb9c1"},"schema_version":"1.0","source":{"id":"2402.12867","kind":"arxiv","version":1}},"canonical_sha256":"3dae5796aa4ee1a83c2aac624ab9ba271e1c81267f401dd88b510bd2164a3b54","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3dae5796aa4ee1a83c2aac624ab9ba271e1c81267f401dd88b510bd2164a3b54","first_computed_at":"2026-07-05T07:47:17.560183Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:47:17.560183Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"He8ShKyIiSxOGGr1hfiemuzOfhBjXAS+fvk2wkczOlRemCFmXMEcjSn2VlmhSdupdBIFIChbuNaissv2y4zGCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:47:17.560644Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.12867","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:56c9e3ca582f4c9e20a59fcb51d3301124fa6353b7af91cd3d5e1a694aeb4751","sha256:18af4be180a9d1f632983cae4cd1302b4e031c59acaebb0a3b91451fb46496d0"],"state_sha256":"9aa24a84a5e274135d90b6444d9490573e1c0ae4c1f8f72bfc09292a696f0c38"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dRnEiBM9Baja0vMe5hKk4ReGUv7Pdu6MyFTjHRCKDszAeO7r+ycyBkYL6J8OlTviCu5cJBUZbQgmfe9fKJw5BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T13:08:48.530055Z","bundle_sha256":"0999274a2a607162f95b1e37ad49d91bbdfe7f01ed6d3d72324ea7522eaab39d"}}