{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:FP4ASWCZFFIROMIZP45O2KWZG7","short_pith_number":"pith:FP4ASWCZ","canonical_record":{"source":{"id":"1710.10860","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-30T10:48:02Z","cross_cats_sorted":[],"title_canon_sha256":"e8c50e2f79ceef42e5f8e9c8616e0bcc27f0b397bf9ab753cdba27965d7c9318","abstract_canon_sha256":"9532f64ad60873cf61713483a2b13f1987fee072141efa13bc37b2deb1f5a771"},"schema_version":"1.0"},"canonical_sha256":"2bf809585929511731197f3aed2ad937e1864571a04a5fde1be2569d8fa4aabc","source":{"kind":"arxiv","id":"1710.10860","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.10860","created_at":"2026-05-18T00:31:46Z"},{"alias_kind":"arxiv_version","alias_value":"1710.10860v1","created_at":"2026-05-18T00:31:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.10860","created_at":"2026-05-18T00:31:46Z"},{"alias_kind":"pith_short_12","alias_value":"FP4ASWCZFFIR","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"FP4ASWCZFFIROMIZ","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"FP4ASWCZ","created_at":"2026-05-18T12:31:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:FP4ASWCZFFIROMIZP45O2KWZG7","target":"record","payload":{"canonical_record":{"source":{"id":"1710.10860","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-30T10:48:02Z","cross_cats_sorted":[],"title_canon_sha256":"e8c50e2f79ceef42e5f8e9c8616e0bcc27f0b397bf9ab753cdba27965d7c9318","abstract_canon_sha256":"9532f64ad60873cf61713483a2b13f1987fee072141efa13bc37b2deb1f5a771"},"schema_version":"1.0"},"canonical_sha256":"2bf809585929511731197f3aed2ad937e1864571a04a5fde1be2569d8fa4aabc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:46.270176Z","signature_b64":"aSs4WOCsIDNmAzmWMGNjvymVIRSnJqvLBj9+pxpSAD97g6Un1FaE61iVvPkRvGxCaA0U9g3xINUy2C0GRr7uAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2bf809585929511731197f3aed2ad937e1864571a04a5fde1be2569d8fa4aabc","last_reissued_at":"2026-05-18T00:31:46.269689Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:46.269689Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1710.10860","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":"2026-05-18T00:31:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mxVytq46XYt/hx+VXWTbYUVwNKubzqm0b8Yeg4WZmBT99okv1BIjqVvvHnBt12SZrxGYnIl8WSALhIdal05bBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T09:12:45.090937Z"},"content_sha256":"4daab6d86456ed1dca2646fce281470993fc421700cd0464c38acdd7fe2489a6","schema_version":"1.0","event_id":"sha256:4daab6d86456ed1dca2646fce281470993fc421700cd0464c38acdd7fe2489a6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:FP4ASWCZFFIROMIZP45O2KWZG7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient simulation techniques for biochemical reaction networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.QM","authors_text":"Christopher Lester","submitted_at":"2017-10-30T10:48:02Z","abstract_excerpt":"Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemical processes. The mathematical formulations that such models lead to are opaque, and, due to their complexity, are often considered analytically intractable. As such, a variety of Monte Carlo simulation algorithms have been developed to explore model dynamics empirically. Whilst well-known methods, such as the Gillespie Algorithm, can be implemented to investigate a given model, the computational demands of traditional simulation techniques remain a significant barrier to modern research.\n  In o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.10860","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:31:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VcwaRUsihpLAcXklsN+Pm7dSZ3GHVV+vZGNUAnggVTSNNF9YH2TQvap1YEzqbB1WMrAKKDI/PDloRnvHGIqxBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T09:12:45.091286Z"},"content_sha256":"33bcab743fb226847cb7f2f1d845c0ef02743c2c8feb640b5b38f7cd13cb84e9","schema_version":"1.0","event_id":"sha256:33bcab743fb226847cb7f2f1d845c0ef02743c2c8feb640b5b38f7cd13cb84e9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FP4ASWCZFFIROMIZP45O2KWZG7/bundle.json","state_url":"https://pith.science/pith/FP4ASWCZFFIROMIZP45O2KWZG7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FP4ASWCZFFIROMIZP45O2KWZG7/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":"2026-06-28T09:12:45Z","links":{"resolver":"https://pith.science/pith/FP4ASWCZFFIROMIZP45O2KWZG7","bundle":"https://pith.science/pith/FP4ASWCZFFIROMIZP45O2KWZG7/bundle.json","state":"https://pith.science/pith/FP4ASWCZFFIROMIZP45O2KWZG7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FP4ASWCZFFIROMIZP45O2KWZG7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:FP4ASWCZFFIROMIZP45O2KWZG7","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":"9532f64ad60873cf61713483a2b13f1987fee072141efa13bc37b2deb1f5a771","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-30T10:48:02Z","title_canon_sha256":"e8c50e2f79ceef42e5f8e9c8616e0bcc27f0b397bf9ab753cdba27965d7c9318"},"schema_version":"1.0","source":{"id":"1710.10860","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.10860","created_at":"2026-05-18T00:31:46Z"},{"alias_kind":"arxiv_version","alias_value":"1710.10860v1","created_at":"2026-05-18T00:31:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.10860","created_at":"2026-05-18T00:31:46Z"},{"alias_kind":"pith_short_12","alias_value":"FP4ASWCZFFIR","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"FP4ASWCZFFIROMIZ","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"FP4ASWCZ","created_at":"2026-05-18T12:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:33bcab743fb226847cb7f2f1d845c0ef02743c2c8feb640b5b38f7cd13cb84e9","target":"graph","created_at":"2026-05-18T00:31:46Z","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"},"paper":{"abstract_excerpt":"Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemical processes. The mathematical formulations that such models lead to are opaque, and, due to their complexity, are often considered analytically intractable. As such, a variety of Monte Carlo simulation algorithms have been developed to explore model dynamics empirically. Whilst well-known methods, such as the Gillespie Algorithm, can be implemented to investigate a given model, the computational demands of traditional simulation techniques remain a significant barrier to modern research.\n  In o","authors_text":"Christopher Lester","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-30T10:48:02Z","title":"Efficient simulation techniques for biochemical reaction networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.10860","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":"sha256:4daab6d86456ed1dca2646fce281470993fc421700cd0464c38acdd7fe2489a6","target":"record","created_at":"2026-05-18T00:31:46Z","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":"9532f64ad60873cf61713483a2b13f1987fee072141efa13bc37b2deb1f5a771","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-10-30T10:48:02Z","title_canon_sha256":"e8c50e2f79ceef42e5f8e9c8616e0bcc27f0b397bf9ab753cdba27965d7c9318"},"schema_version":"1.0","source":{"id":"1710.10860","kind":"arxiv","version":1}},"canonical_sha256":"2bf809585929511731197f3aed2ad937e1864571a04a5fde1be2569d8fa4aabc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2bf809585929511731197f3aed2ad937e1864571a04a5fde1be2569d8fa4aabc","first_computed_at":"2026-05-18T00:31:46.269689Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:31:46.269689Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aSs4WOCsIDNmAzmWMGNjvymVIRSnJqvLBj9+pxpSAD97g6Un1FaE61iVvPkRvGxCaA0U9g3xINUy2C0GRr7uAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:31:46.270176Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.10860","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4daab6d86456ed1dca2646fce281470993fc421700cd0464c38acdd7fe2489a6","sha256:33bcab743fb226847cb7f2f1d845c0ef02743c2c8feb640b5b38f7cd13cb84e9"],"state_sha256":"4c8ee065606e62576fae62354e571bdc6738fb8fae54483369c0b5d7764a4ec2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fdg7J3wK0XMjQcGQtpMQI7qaJEQNrchhpOOdHRgNAHkx3txs7nb1XEVvumBwmZb2cwLjwpG9e/UPCqRCOmY7DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T09:12:45.093120Z","bundle_sha256":"fc4c681f5eaf105a6aeec55cc4dbbdf79836182a36290a88a71a99e38fca532f"}}