{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:R2KWI2JALDUNMYZFHZ3QTDZ2FE","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":"4327cd8815104072af26e1c569a58e12c32f4cee047af06dd001ce283e56a672","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-06-24T15:05:39Z","title_canon_sha256":"09a55181be99d97d4d912bfac3b3129ac3feb3ec1d94cc50b371d404b426bbae"},"schema_version":"1.0","source":{"id":"2007.04921","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.04921","created_at":"2026-07-05T04:11:04Z"},{"alias_kind":"arxiv_version","alias_value":"2007.04921v3","created_at":"2026-07-05T04:11:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.04921","created_at":"2026-07-05T04:11:04Z"},{"alias_kind":"pith_short_12","alias_value":"R2KWI2JALDUN","created_at":"2026-07-05T04:11:04Z"},{"alias_kind":"pith_short_16","alias_value":"R2KWI2JALDUNMYZF","created_at":"2026-07-05T04:11:04Z"},{"alias_kind":"pith_short_8","alias_value":"R2KWI2JA","created_at":"2026-07-05T04:11:04Z"}],"graph_snapshots":[{"event_id":"sha256:0bbecc4d46dce8560dae468294b22a28c39acb20aa10e6543dc1ab7e1175e4dd","target":"graph","created_at":"2026-07-05T04:11:04Z","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/2007.04921/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The selection of coarse-grained (CG) mapping operators is a critical step for CG molecular dynamics (MD) simulation. It is still an open question about what is optimal for this choice and there is a need for theory. The current state-of-the art method is mapping operators manually selected by experts. In this work, we demonstrate an automated approach by viewing this problem as supervised learning where we seek to reproduce the mapping operators produced by experts. We present a graph neural network based CG mapping predictor called DEEP SUPERVISED GRAPH PARTITIONING MODEL(DSGPM) that treats m","authors_text":"Andrew D. White, Chenliang Xu, Geemi P. Wellawatte, Heta A. Gandhi, Maghesree Chakraborty, Zhiheng Li","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-06-24T15:05:39Z","title":"Graph Neural Network Based Coarse-Grained Mapping Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.04921","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":"sha256:511159104017b51331b147d8b29519dc8b69f819216224f1d2074b7f981f5e06","target":"record","created_at":"2026-07-05T04:11:04Z","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":"4327cd8815104072af26e1c569a58e12c32f4cee047af06dd001ce283e56a672","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-06-24T15:05:39Z","title_canon_sha256":"09a55181be99d97d4d912bfac3b3129ac3feb3ec1d94cc50b371d404b426bbae"},"schema_version":"1.0","source":{"id":"2007.04921","kind":"arxiv","version":3}},"canonical_sha256":"8e9564692058e8d663253e77098f3a293a90c53ec357d7ad97e02c4f041ff251","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e9564692058e8d663253e77098f3a293a90c53ec357d7ad97e02c4f041ff251","first_computed_at":"2026-07-05T04:11:04.155304Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:11:04.155304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8++GZugTWwqaxUOWWfxKh2DNUxEfJy8jsWsLg2aCZQtnhQzNM7NrguTI0eOY9SHeS4vU3wWFIM0Yhnv/BABwCw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:11:04.155796Z","signed_message":"canonical_sha256_bytes"},"source_id":"2007.04921","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:511159104017b51331b147d8b29519dc8b69f819216224f1d2074b7f981f5e06","sha256:0bbecc4d46dce8560dae468294b22a28c39acb20aa10e6543dc1ab7e1175e4dd"],"state_sha256":"597770f9608a0e9a380fed9fd6bfabcdcecba8b9032fdb79b901bd6db74c855f"}