{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:VJQKTAYFXQCVQYUFVFZ4ECICTY","short_pith_number":"pith:VJQKTAYF","schema_version":"1.0","canonical_sha256":"aa60a98305bc05586285a973c209029e35f73b24a35ba6b5b75d70b19f0f270f","source":{"kind":"arxiv","id":"2506.20341","version":1},"attestation_state":"computed","paper":{"title":"A Neural-Operator Surrogate for Platelet Deformation Across Capillary Numbers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.flu-dyn","authors_text":"Marco Laudato","submitted_at":"2025-06-25T11:49:57Z","abstract_excerpt":"Reliable multiscale models of thrombosis require platelet-scale fidelity at organ-scale cost, a gap that scientific machine learning has the potential to narrow. We train a DeepONet surrogate on platelet dynamics generated with LAMMPS for platelets spanning ten elastic moduli and capillary numbers (0.07 - 0.77). The network takes in input the wall shear stress, bond stiffness, time, and initial particle coordinates and returns the full three-dimensional deformation of the membrane. Mean-squared-error minimization with Adam and adaptive learning-rate decay yields a median displacement error bel"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.20341","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.flu-dyn","submitted_at":"2025-06-25T11:49:57Z","cross_cats_sorted":[],"title_canon_sha256":"a47f4033300337c83ef22a745fb43219cecce75fc31ccf77a58c0a9bcd8f6dc6","abstract_canon_sha256":"ce55a3f1b530a6e20c7ba1871191ed4e4420dd94a4c1e6f92d3564ff0835246c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:27:03.989380Z","signature_b64":"gTxObN3Bi6ykufkiyU0NXiR2hWn7UU+57R99Ffxqw8bnwFNG7WuLiTdU8X/YQTgEFR3rfVTWmLPlOkHTlVgYDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa60a98305bc05586285a973c209029e35f73b24a35ba6b5b75d70b19f0f270f","last_reissued_at":"2026-07-05T11:27:03.988888Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:27:03.988888Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Neural-Operator Surrogate for Platelet Deformation Across Capillary Numbers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.flu-dyn","authors_text":"Marco Laudato","submitted_at":"2025-06-25T11:49:57Z","abstract_excerpt":"Reliable multiscale models of thrombosis require platelet-scale fidelity at organ-scale cost, a gap that scientific machine learning has the potential to narrow. We train a DeepONet surrogate on platelet dynamics generated with LAMMPS for platelets spanning ten elastic moduli and capillary numbers (0.07 - 0.77). The network takes in input the wall shear stress, bond stiffness, time, and initial particle coordinates and returns the full three-dimensional deformation of the membrane. Mean-squared-error minimization with Adam and adaptive learning-rate decay yields a median displacement error bel"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.20341","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/2506.20341/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.20341","created_at":"2026-07-05T11:27:03.988945+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.20341v1","created_at":"2026-07-05T11:27:03.988945+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.20341","created_at":"2026-07-05T11:27:03.988945+00:00"},{"alias_kind":"pith_short_12","alias_value":"VJQKTAYFXQCV","created_at":"2026-07-05T11:27:03.988945+00:00"},{"alias_kind":"pith_short_16","alias_value":"VJQKTAYFXQCVQYUF","created_at":"2026-07-05T11:27:03.988945+00:00"},{"alias_kind":"pith_short_8","alias_value":"VJQKTAYF","created_at":"2026-07-05T11:27:03.988945+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY","json":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY.json","graph_json":"https://pith.science/api/pith-number/VJQKTAYFXQCVQYUFVFZ4ECICTY/graph.json","events_json":"https://pith.science/api/pith-number/VJQKTAYFXQCVQYUFVFZ4ECICTY/events.json","paper":"https://pith.science/paper/VJQKTAYF"},"agent_actions":{"view_html":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY","download_json":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY.json","view_paper":"https://pith.science/paper/VJQKTAYF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.20341&json=true","fetch_graph":"https://pith.science/api/pith-number/VJQKTAYFXQCVQYUFVFZ4ECICTY/graph.json","fetch_events":"https://pith.science/api/pith-number/VJQKTAYFXQCVQYUFVFZ4ECICTY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY/action/storage_attestation","attest_author":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY/action/author_attestation","sign_citation":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY/action/citation_signature","submit_replication":"https://pith.science/pith/VJQKTAYFXQCVQYUFVFZ4ECICTY/action/replication_record"}},"created_at":"2026-07-05T11:27:03.988945+00:00","updated_at":"2026-07-05T11:27:03.988945+00:00"}