{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:CZDBSABYFNJ7DYRK343YFZZQDJ","short_pith_number":"pith:CZDBSABY","canonical_record":{"source":{"id":"2309.03840","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2023-09-07T16:54:43Z","cross_cats_sorted":["cond-mat.mtrl-sci"],"title_canon_sha256":"763f69bafa90c4fa74d14c6818ef9443809e38b9b9e362e5dc47376581463e2f","abstract_canon_sha256":"854700a619532f2acb02d1d7ce703d3815b372513fce4de3ff82eba0ccc3ce91"},"schema_version":"1.0"},"canonical_sha256":"16461900382b53f1e22adf3782e7301a55592aee934014e792e83dab5557b3e3","source":{"kind":"arxiv","id":"2309.03840","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.03840","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"arxiv_version","alias_value":"2309.03840v1","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.03840","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"pith_short_12","alias_value":"CZDBSABYFNJ7","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"pith_short_16","alias_value":"CZDBSABYFNJ7DYRK","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"pith_short_8","alias_value":"CZDBSABY","created_at":"2026-07-05T06:48:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:CZDBSABYFNJ7DYRK343YFZZQDJ","target":"record","payload":{"canonical_record":{"source":{"id":"2309.03840","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2023-09-07T16:54:43Z","cross_cats_sorted":["cond-mat.mtrl-sci"],"title_canon_sha256":"763f69bafa90c4fa74d14c6818ef9443809e38b9b9e362e5dc47376581463e2f","abstract_canon_sha256":"854700a619532f2acb02d1d7ce703d3815b372513fce4de3ff82eba0ccc3ce91"},"schema_version":"1.0"},"canonical_sha256":"16461900382b53f1e22adf3782e7301a55592aee934014e792e83dab5557b3e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:48:42.754764Z","signature_b64":"IICs73ue2u8aynPILVFn7lSVdgg5dMFfQrHuEIys/eT2NZmh6trDjiftCHU/DFfBEv+Lvw7d6l0M2lfudiKeDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"16461900382b53f1e22adf3782e7301a55592aee934014e792e83dab5557b3e3","last_reissued_at":"2026-07-05T06:48:42.754365Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:48:42.754365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.03840","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":"2026-07-05T06:48:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G4ewbreWBg16L89vK5Bw0EQ8eIOWInMcUK1eS/5ow+H3Bfd7IO7jeqVkF7JvOs5aSrfYKdzRTRKICsJ2A5uxDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T14:34:14.950355Z"},"content_sha256":"b1598dce96753f00c61927879894b700a53d647b179dedb7d72cdd05e3cb3834","schema_version":"1.0","event_id":"sha256:b1598dce96753f00c61927879894b700a53d647b179dedb7d72cdd05e3cb3834"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:CZDBSABYFNJ7DYRK343YFZZQDJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generating Minimal Training Sets for Machine Learned Potentials","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.mtrl-sci"],"primary_cat":"physics.comp-ph","authors_text":"Christian Holm, Jan Finkbeiner, Samuel Tovey","submitted_at":"2023-09-07T16:54:43Z","abstract_excerpt":"This letter presents a novel approach for identifying uncorrelated atomic configurations from extensive data sets with a non-standard neural network workflow known as random network distillation (RND) for training machine-learned inter-atomic potentials (MLPs). This method is coupled with a DFT workflow wherein initial data is generated with cheaper classical methods before only the minimal subset is passed to a more computationally expensive ab initio calculation. This benefits training not only by reducing the number of expensive DFT calculations required but also by providing a pathway to t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.03840","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/2309.03840/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":"2026-07-05T06:48:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x8hz1c4pncFdaMxLQs7kTQdupfc42FAp17rHgKFIEtpjFN4d1mbyb8SyOjmH9oGJEWsGjUTjbus1wmjOgS8BAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T14:34:14.951491Z"},"content_sha256":"f93764106bfd61d64493e52f88cffbb62bdd332782357b997738627511e3388a","schema_version":"1.0","event_id":"sha256:f93764106bfd61d64493e52f88cffbb62bdd332782357b997738627511e3388a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CZDBSABYFNJ7DYRK343YFZZQDJ/bundle.json","state_url":"https://pith.science/pith/CZDBSABYFNJ7DYRK343YFZZQDJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CZDBSABYFNJ7DYRK343YFZZQDJ/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":"2026-08-17T14:34:14Z","links":{"resolver":"https://pith.science/pith/CZDBSABYFNJ7DYRK343YFZZQDJ","bundle":"https://pith.science/pith/CZDBSABYFNJ7DYRK343YFZZQDJ/bundle.json","state":"https://pith.science/pith/CZDBSABYFNJ7DYRK343YFZZQDJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CZDBSABYFNJ7DYRK343YFZZQDJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CZDBSABYFNJ7DYRK343YFZZQDJ","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":"854700a619532f2acb02d1d7ce703d3815b372513fce4de3ff82eba0ccc3ce91","cross_cats_sorted":["cond-mat.mtrl-sci"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2023-09-07T16:54:43Z","title_canon_sha256":"763f69bafa90c4fa74d14c6818ef9443809e38b9b9e362e5dc47376581463e2f"},"schema_version":"1.0","source":{"id":"2309.03840","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.03840","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"arxiv_version","alias_value":"2309.03840v1","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.03840","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"pith_short_12","alias_value":"CZDBSABYFNJ7","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"pith_short_16","alias_value":"CZDBSABYFNJ7DYRK","created_at":"2026-07-05T06:48:42Z"},{"alias_kind":"pith_short_8","alias_value":"CZDBSABY","created_at":"2026-07-05T06:48:42Z"}],"graph_snapshots":[{"event_id":"sha256:f93764106bfd61d64493e52f88cffbb62bdd332782357b997738627511e3388a","target":"graph","created_at":"2026-07-05T06:48:42Z","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/2309.03840/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This letter presents a novel approach for identifying uncorrelated atomic configurations from extensive data sets with a non-standard neural network workflow known as random network distillation (RND) for training machine-learned inter-atomic potentials (MLPs). This method is coupled with a DFT workflow wherein initial data is generated with cheaper classical methods before only the minimal subset is passed to a more computationally expensive ab initio calculation. This benefits training not only by reducing the number of expensive DFT calculations required but also by providing a pathway to t","authors_text":"Christian Holm, Jan Finkbeiner, Samuel Tovey","cross_cats":["cond-mat.mtrl-sci"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2023-09-07T16:54:43Z","title":"Generating Minimal Training Sets for Machine Learned Potentials"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.03840","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:b1598dce96753f00c61927879894b700a53d647b179dedb7d72cdd05e3cb3834","target":"record","created_at":"2026-07-05T06:48:42Z","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":"854700a619532f2acb02d1d7ce703d3815b372513fce4de3ff82eba0ccc3ce91","cross_cats_sorted":["cond-mat.mtrl-sci"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2023-09-07T16:54:43Z","title_canon_sha256":"763f69bafa90c4fa74d14c6818ef9443809e38b9b9e362e5dc47376581463e2f"},"schema_version":"1.0","source":{"id":"2309.03840","kind":"arxiv","version":1}},"canonical_sha256":"16461900382b53f1e22adf3782e7301a55592aee934014e792e83dab5557b3e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16461900382b53f1e22adf3782e7301a55592aee934014e792e83dab5557b3e3","first_computed_at":"2026-07-05T06:48:42.754365Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:48:42.754365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IICs73ue2u8aynPILVFn7lSVdgg5dMFfQrHuEIys/eT2NZmh6trDjiftCHU/DFfBEv+Lvw7d6l0M2lfudiKeDA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:48:42.754764Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.03840","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b1598dce96753f00c61927879894b700a53d647b179dedb7d72cdd05e3cb3834","sha256:f93764106bfd61d64493e52f88cffbb62bdd332782357b997738627511e3388a"],"state_sha256":"58650016ef460fb3db6494d951cefc08d9a44811cd90db62b0b407556282df2d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zr+IQTfhy6NSl+BXBkVQuuodzWRgt1OUr9hnrMJ9+UbCY8QSsLotH7XfG6EGAAkHrFODevCkCfgv15qYzwlOCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T14:34:14.960563Z","bundle_sha256":"e8576ebf00b5c24e52a18ac4e33a24c60a66734bcd83c571eff0b5f5bef544b1"}}