{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:YZCZDMDMU7L6AZXA4OA2C56YSV","short_pith_number":"pith:YZCZDMDM","schema_version":"1.0","canonical_sha256":"c64591b06ca7d7e066e0e381a177d89548f316a7849e6198edd4350176bdb406","source":{"kind":"arxiv","id":"1710.05100","version":1},"attestation_state":"computed","paper":{"title":"Neural network dose models for knowledge-based planning in pancreatic SBRT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Bernard L. Jones, Karyn A. Goodman, Lindsey Olsen, Moyed Miften, Priscilla Stumpf, Tracey Schefter, Warren G. Campbell","submitted_at":"2017-10-13T23:28:47Z","abstract_excerpt":"Stereotactic body radiation therapy (SBRT) for pancreatic cancer requires a skillful approach to deliver ablative doses to the tumor while limiting dose to the highly sensitive duodenum, stomach, and small bowel. Here, we develop knowledge-based artificial neural network dose models (ANN-DMs) to predict dose distributions that would be approved by experienced physicians. Using dose distributions calculated by a commercial treatment planning system (TPS), physician-approved treatment plans were used to train ANN-DMs that could predict physician-approved dose distributions based on a set of geom"},"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":"1710.05100","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2017-10-13T23:28:47Z","cross_cats_sorted":[],"title_canon_sha256":"a4dc3a45bb35211f0bbe9218ab3a80405e7d48d776c54819b0cf027fabf44b3e","abstract_canon_sha256":"9d23871e3d23c1a829ea0b13b940280be904bbe80a299dd592da5b2d614295fe"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:54.390389Z","signature_b64":"vnphpsKlapBM/EgHKw8dFIsegp3Zfr4Ktdfi+IQgd07rvZXV7nmnPsLe8FlPUrIJ6w8rlGZ+1F/g/O30sM/rDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c64591b06ca7d7e066e0e381a177d89548f316a7849e6198edd4350176bdb406","last_reissued_at":"2026-05-18T00:32:54.389726Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:54.389726Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Neural network dose models for knowledge-based planning in pancreatic SBRT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Bernard L. Jones, Karyn A. Goodman, Lindsey Olsen, Moyed Miften, Priscilla Stumpf, Tracey Schefter, Warren G. Campbell","submitted_at":"2017-10-13T23:28:47Z","abstract_excerpt":"Stereotactic body radiation therapy (SBRT) for pancreatic cancer requires a skillful approach to deliver ablative doses to the tumor while limiting dose to the highly sensitive duodenum, stomach, and small bowel. Here, we develop knowledge-based artificial neural network dose models (ANN-DMs) to predict dose distributions that would be approved by experienced physicians. Using dose distributions calculated by a commercial treatment planning system (TPS), physician-approved treatment plans were used to train ANN-DMs that could predict physician-approved dose distributions based on a set of geom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.05100","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":""},"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":"1710.05100","created_at":"2026-05-18T00:32:54.389827+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.05100v1","created_at":"2026-05-18T00:32:54.389827+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.05100","created_at":"2026-05-18T00:32:54.389827+00:00"},{"alias_kind":"pith_short_12","alias_value":"YZCZDMDMU7L6","created_at":"2026-05-18T12:31:59.375834+00:00"},{"alias_kind":"pith_short_16","alias_value":"YZCZDMDMU7L6AZXA","created_at":"2026-05-18T12:31:59.375834+00:00"},{"alias_kind":"pith_short_8","alias_value":"YZCZDMDM","created_at":"2026-05-18T12:31:59.375834+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/YZCZDMDMU7L6AZXA4OA2C56YSV","json":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV.json","graph_json":"https://pith.science/api/pith-number/YZCZDMDMU7L6AZXA4OA2C56YSV/graph.json","events_json":"https://pith.science/api/pith-number/YZCZDMDMU7L6AZXA4OA2C56YSV/events.json","paper":"https://pith.science/paper/YZCZDMDM"},"agent_actions":{"view_html":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV","download_json":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV.json","view_paper":"https://pith.science/paper/YZCZDMDM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.05100&json=true","fetch_graph":"https://pith.science/api/pith-number/YZCZDMDMU7L6AZXA4OA2C56YSV/graph.json","fetch_events":"https://pith.science/api/pith-number/YZCZDMDMU7L6AZXA4OA2C56YSV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV/action/storage_attestation","attest_author":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV/action/author_attestation","sign_citation":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV/action/citation_signature","submit_replication":"https://pith.science/pith/YZCZDMDMU7L6AZXA4OA2C56YSV/action/replication_record"}},"created_at":"2026-05-18T00:32:54.389827+00:00","updated_at":"2026-05-18T00:32:54.389827+00:00"}