{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6VJOCTFI2BCSM4TO47GTSIXDIB","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":"d5c427a2af2634218ebc0488a8a7b160728c0e1434d2c0d031d87bb668822f6c","cross_cats_sorted":["cs.LG","math.AT","physics.comp-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2020-10-01T16:31:46Z","title_canon_sha256":"d79a0f69750b3924d0c71cc8683325f23f8b35952829b056f13bbb17b950bad1"},"schema_version":"1.0","source":{"id":"2010.00532","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.00532","created_at":"2026-07-05T02:28:06Z"},{"alias_kind":"arxiv_version","alias_value":"2010.00532v2","created_at":"2026-07-05T02:28:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.00532","created_at":"2026-07-05T02:28:06Z"},{"alias_kind":"pith_short_12","alias_value":"6VJOCTFI2BCS","created_at":"2026-07-05T02:28:06Z"},{"alias_kind":"pith_short_16","alias_value":"6VJOCTFI2BCSM4TO","created_at":"2026-07-05T02:28:06Z"},{"alias_kind":"pith_short_8","alias_value":"6VJOCTFI","created_at":"2026-07-05T02:28:06Z"}],"graph_snapshots":[{"event_id":"sha256:afc0f52e0748644ef6f2b9b122cd145aac497d9da3a62d626cee0f9384b7c9f2","target":"graph","created_at":"2026-07-05T02:28:06Z","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/2010.00532/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an end-to-end machine learning model that automatically generates descriptors that capture a complex representation of a material's structure and chemistry. This approach builds on computational topology techniques (namely, persistent homology) and word embeddings from natural language processing. It automatically encapsulates geometric and chemical information directly","authors_text":"Aditi S. Krishnapriyan, Dmitriy Morozov, Jens Hummelsh{\\o}j, Joseph Montoya, Maciej Haranczyk","cross_cats":["cs.LG","math.AT","physics.comp-ph"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2020-10-01T16:31:46Z","title":"Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.00532","kind":"arxiv","version":2},"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":"sha256:36c7faad0a8edf9afe360e89668f3e0d7ee2635e4d410e963622e5c1014e33fc","target":"record","created_at":"2026-07-05T02:28:06Z","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":"d5c427a2af2634218ebc0488a8a7b160728c0e1434d2c0d031d87bb668822f6c","cross_cats_sorted":["cs.LG","math.AT","physics.comp-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2020-10-01T16:31:46Z","title_canon_sha256":"d79a0f69750b3924d0c71cc8683325f23f8b35952829b056f13bbb17b950bad1"},"schema_version":"1.0","source":{"id":"2010.00532","kind":"arxiv","version":2}},"canonical_sha256":"f552e14ca8d04526726ee7cd3922e34065dd6aca68e980d4556aafaa9017ce30","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f552e14ca8d04526726ee7cd3922e34065dd6aca68e980d4556aafaa9017ce30","first_computed_at":"2026-07-05T02:28:06.082982Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:28:06.082982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wQv+sM6H/dFFToaVFH1AeE0k6f55BPFhyvKwFgFBH2oMiECtTwaAaoaa0DsoUJYbsp/+SfLqG9QqWdNrJZi5BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:28:06.083458Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.00532","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:36c7faad0a8edf9afe360e89668f3e0d7ee2635e4d410e963622e5c1014e33fc","sha256:afc0f52e0748644ef6f2b9b122cd145aac497d9da3a62d626cee0f9384b7c9f2"],"state_sha256":"80dc5da9cc69aeb589d4d499063f65b6515c42869f9d82e39ec78e74b918de79"}