{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SATLLSHOEKXPKEMNCAJJEBV7ET","short_pith_number":"pith:SATLLSHO","canonical_record":{"source":{"id":"2506.05203","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LO","submitted_at":"2025-06-05T16:14:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"55103baa21c0c7f8720fed719f557bc84496feca587f75070b59761f1fdb5bba","abstract_canon_sha256":"2cf419896b63f51ce08b2430924752a6a0a47c8ef98e9b4fd4405d0b0de0a60c"},"schema_version":"1.0"},"canonical_sha256":"9026b5c8ee22aef5118d10129206bf24f02088d443c5720266765fad1666522f","source":{"kind":"arxiv","id":"2506.05203","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05203","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05203v1","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05203","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"pith_short_12","alias_value":"SATLLSHOEKXP","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"pith_short_16","alias_value":"SATLLSHOEKXPKEMN","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"pith_short_8","alias_value":"SATLLSHO","created_at":"2026-07-05T11:16:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SATLLSHOEKXPKEMNCAJJEBV7ET","target":"record","payload":{"canonical_record":{"source":{"id":"2506.05203","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LO","submitted_at":"2025-06-05T16:14:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"55103baa21c0c7f8720fed719f557bc84496feca587f75070b59761f1fdb5bba","abstract_canon_sha256":"2cf419896b63f51ce08b2430924752a6a0a47c8ef98e9b4fd4405d0b0de0a60c"},"schema_version":"1.0"},"canonical_sha256":"9026b5c8ee22aef5118d10129206bf24f02088d443c5720266765fad1666522f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:16:43.931815Z","signature_b64":"eDVREcJCYlp3/ukAfsGW/Vr9wcz9BeTXVfK2dh7V3xBS1/ARfHxZFm4OIVbgD84HVY7dmCAPZsukSVBwHPJ6Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9026b5c8ee22aef5118d10129206bf24f02088d443c5720266765fad1666522f","last_reissued_at":"2026-07-05T11:16:43.931311Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:16:43.931311Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.05203","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":"2026-07-05T11:16:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ApHWkvDg1IaIMad2xFthvXKfobNfZOImHP83gldNQ6vy9oZHY1G/mIi+Czw9K9YQ9OYZg7PluFIw+RajvL36Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T04:16:27.845677Z"},"content_sha256":"6b1302818cdeec833134b0a02978b222787ccae913eac7f81c52cfd56d3dfbaa","schema_version":"1.0","event_id":"sha256:6b1302818cdeec833134b0a02978b222787ccae913eac7f81c52cfd56d3dfbaa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SATLLSHOEKXPKEMNCAJJEBV7ET","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Trustworthiness Preservation by Copies of Machine Learning Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.LO","authors_text":"Giuseppe Primiero, Leonardo Ceragioli","submitted_at":"2025-06-05T16:14:57Z","abstract_excerpt":"A common practice of ML systems development concerns the training of the same model under different data sets, and the use of the same (training and test) sets for different learning models. The first case is a desirable practice for identifying high quality and unbiased training conditions. The latter case coincides with the search for optimal models under a common dataset for training. These differently obtained systems have been considered akin to copies. In the quest for responsible AI, a legitimate but hardly investigated question is how to verify that trustworthiness is preserved by copi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05203","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/2506.05203/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":"2026-07-05T11:16:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m7hdjNnnTVuVNO+C/L4tKxVX/EoFzrBmlrxgqT4gGx0YtjzLiC9ghOGYLF0xRx36eQI9vpRkhXr2Hu+CT/veAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T04:16:27.846223Z"},"content_sha256":"213b384f5c401ca94848edaa16f6fe937b8d36a57a13da449cbbee43adfc9d4f","schema_version":"1.0","event_id":"sha256:213b384f5c401ca94848edaa16f6fe937b8d36a57a13da449cbbee43adfc9d4f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SATLLSHOEKXPKEMNCAJJEBV7ET/bundle.json","state_url":"https://pith.science/pith/SATLLSHOEKXPKEMNCAJJEBV7ET/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SATLLSHOEKXPKEMNCAJJEBV7ET/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":"2026-08-09T04:16:27Z","links":{"resolver":"https://pith.science/pith/SATLLSHOEKXPKEMNCAJJEBV7ET","bundle":"https://pith.science/pith/SATLLSHOEKXPKEMNCAJJEBV7ET/bundle.json","state":"https://pith.science/pith/SATLLSHOEKXPKEMNCAJJEBV7ET/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SATLLSHOEKXPKEMNCAJJEBV7ET/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SATLLSHOEKXPKEMNCAJJEBV7ET","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":"2cf419896b63f51ce08b2430924752a6a0a47c8ef98e9b4fd4405d0b0de0a60c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LO","submitted_at":"2025-06-05T16:14:57Z","title_canon_sha256":"55103baa21c0c7f8720fed719f557bc84496feca587f75070b59761f1fdb5bba"},"schema_version":"1.0","source":{"id":"2506.05203","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05203","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05203v1","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05203","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"pith_short_12","alias_value":"SATLLSHOEKXP","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"pith_short_16","alias_value":"SATLLSHOEKXPKEMN","created_at":"2026-07-05T11:16:43Z"},{"alias_kind":"pith_short_8","alias_value":"SATLLSHO","created_at":"2026-07-05T11:16:43Z"}],"graph_snapshots":[{"event_id":"sha256:213b384f5c401ca94848edaa16f6fe937b8d36a57a13da449cbbee43adfc9d4f","target":"graph","created_at":"2026-07-05T11:16:43Z","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/2506.05203/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A common practice of ML systems development concerns the training of the same model under different data sets, and the use of the same (training and test) sets for different learning models. The first case is a desirable practice for identifying high quality and unbiased training conditions. The latter case coincides with the search for optimal models under a common dataset for training. These differently obtained systems have been considered akin to copies. In the quest for responsible AI, a legitimate but hardly investigated question is how to verify that trustworthiness is preserved by copi","authors_text":"Giuseppe Primiero, Leonardo Ceragioli","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LO","submitted_at":"2025-06-05T16:14:57Z","title":"Trustworthiness Preservation by Copies of Machine Learning Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05203","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":"sha256:6b1302818cdeec833134b0a02978b222787ccae913eac7f81c52cfd56d3dfbaa","target":"record","created_at":"2026-07-05T11:16:43Z","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":"2cf419896b63f51ce08b2430924752a6a0a47c8ef98e9b4fd4405d0b0de0a60c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LO","submitted_at":"2025-06-05T16:14:57Z","title_canon_sha256":"55103baa21c0c7f8720fed719f557bc84496feca587f75070b59761f1fdb5bba"},"schema_version":"1.0","source":{"id":"2506.05203","kind":"arxiv","version":1}},"canonical_sha256":"9026b5c8ee22aef5118d10129206bf24f02088d443c5720266765fad1666522f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9026b5c8ee22aef5118d10129206bf24f02088d443c5720266765fad1666522f","first_computed_at":"2026-07-05T11:16:43.931311Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:16:43.931311Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eDVREcJCYlp3/ukAfsGW/Vr9wcz9BeTXVfK2dh7V3xBS1/ARfHxZFm4OIVbgD84HVY7dmCAPZsukSVBwHPJ6Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:16:43.931815Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.05203","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b1302818cdeec833134b0a02978b222787ccae913eac7f81c52cfd56d3dfbaa","sha256:213b384f5c401ca94848edaa16f6fe937b8d36a57a13da449cbbee43adfc9d4f"],"state_sha256":"6c2d8bbe669e975eac78191cc932a95469fb4847f9b3c5cb902791e9c8cd6719"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V7vUS9tvc6oCyDbt9BarHzRLpul7RssjEza33Jpez2NLtycxVyLD/EeZX/EvqIHYg6tdNP3FBibeG7l8srhIDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T04:16:27.849807Z","bundle_sha256":"5d238d44b09ae1196633bee16ededed7c81e15f2f97f10c4fb7c20e9bf224164"}}