{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:7AAXE7YIBBCE5T27IG2NAA2EEW","short_pith_number":"pith:7AAXE7YI","canonical_record":{"source":{"id":"1707.04362","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-07-14T01:03:04Z","cross_cats_sorted":["cs.CG","math.AT"],"title_canon_sha256":"e56fbe48add8ca1c1e7dabb7d010d6a4cacd77ed82275acce5727431af2eb555","abstract_canon_sha256":"35a2e24f8e679daaf0c51c50b05a93a12f8e0408e7d7ad1ed98c6e61a8bdb708"},"schema_version":"1.0"},"canonical_sha256":"f801727f0808444ecf5f41b4d00344259a38426fccf2a98cd2ab64438522f16c","source":{"kind":"arxiv","id":"1707.04362","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.04362","created_at":"2026-05-17T23:44:10Z"},{"alias_kind":"arxiv_version","alias_value":"1707.04362v2","created_at":"2026-05-17T23:44:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.04362","created_at":"2026-05-17T23:44:10Z"},{"alias_kind":"pith_short_12","alias_value":"7AAXE7YIBBCE","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"7AAXE7YIBBCE5T27","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"7AAXE7YI","created_at":"2026-05-18T12:31:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:7AAXE7YIBBCE5T27IG2NAA2EEW","target":"record","payload":{"canonical_record":{"source":{"id":"1707.04362","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-07-14T01:03:04Z","cross_cats_sorted":["cs.CG","math.AT"],"title_canon_sha256":"e56fbe48add8ca1c1e7dabb7d010d6a4cacd77ed82275acce5727431af2eb555","abstract_canon_sha256":"35a2e24f8e679daaf0c51c50b05a93a12f8e0408e7d7ad1ed98c6e61a8bdb708"},"schema_version":"1.0"},"canonical_sha256":"f801727f0808444ecf5f41b4d00344259a38426fccf2a98cd2ab64438522f16c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:10.429730Z","signature_b64":"sAYSdCVpF1di8c4ib8NKM9k69C+2dqv3QmweYKCYnp4PKI5yjkjlGxw95oT6x+h/c1NzhfKMuVo0GQQwzjARAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f801727f0808444ecf5f41b4d00344259a38426fccf2a98cd2ab64438522f16c","last_reissued_at":"2026-05-17T23:44:10.429056Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:10.429056Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.04362","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G3wkK9FCVzxpwk30cQHXZzCDQVvsiKA1Uvw6PvVeA6AFxr5qQgyku34N0J8Oignsa8AOjlwlP0DTYfnUZevbAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T08:33:33.060215Z"},"content_sha256":"6b4106c9d896ed7c49a8d632c2c68eece79dc0a21ddfb4b61d3a26476466093d","schema_version":"1.0","event_id":"sha256:6b4106c9d896ed7c49a8d632c2c68eece79dc0a21ddfb4b61d3a26476466093d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:7AAXE7YIBBCE5T27IG2NAA2EEW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hyppo-X: A Scalable Exploratory Framework for Analyzing Complex Phenomics Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CG","math.AT"],"primary_cat":"q-bio.QM","authors_text":"Ananth Kalyanaraman, Bala Krishnamoorthy, Methun Kamruzzaman, Patrick Schnable, Stefan Hey","submitted_at":"2017-07-14T01:03:04Z","abstract_excerpt":"Phenomics is an emerging branch of modern biology that uses high throughput phenotyping tools to capture multiple environmental and phenotypic traits, often at massive spatial and temporal scales. The resulting high dimensional data represent a treasure trove of information for providing an in-depth understanding of how multiple factors interact and contribute to the overall growth and behavior of different genotypes. However, computational tools that can parse through such complex data and aid in extracting plausible hypotheses are currently lacking. In this paper, we present Hyppo-X, a new a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.04362","kind":"arxiv","version":2},"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":"2026-05-17T23:44:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EPC7u073bKBR613exRcS4rmbfauKY44J8WxzyBU4pGfOHtVRjrKAiz5CRTDWz/lrJd4WVMcn5sx/n9sfxQqfAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T08:33:33.060580Z"},"content_sha256":"e5759970d744b2cd6da0a6592c7ffb143b22ef9893b548ca8887893ad3179d30","schema_version":"1.0","event_id":"sha256:e5759970d744b2cd6da0a6592c7ffb143b22ef9893b548ca8887893ad3179d30"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7AAXE7YIBBCE5T27IG2NAA2EEW/bundle.json","state_url":"https://pith.science/pith/7AAXE7YIBBCE5T27IG2NAA2EEW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7AAXE7YIBBCE5T27IG2NAA2EEW/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":"2026-06-30T08:33:33Z","links":{"resolver":"https://pith.science/pith/7AAXE7YIBBCE5T27IG2NAA2EEW","bundle":"https://pith.science/pith/7AAXE7YIBBCE5T27IG2NAA2EEW/bundle.json","state":"https://pith.science/pith/7AAXE7YIBBCE5T27IG2NAA2EEW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7AAXE7YIBBCE5T27IG2NAA2EEW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:7AAXE7YIBBCE5T27IG2NAA2EEW","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":"35a2e24f8e679daaf0c51c50b05a93a12f8e0408e7d7ad1ed98c6e61a8bdb708","cross_cats_sorted":["cs.CG","math.AT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-07-14T01:03:04Z","title_canon_sha256":"e56fbe48add8ca1c1e7dabb7d010d6a4cacd77ed82275acce5727431af2eb555"},"schema_version":"1.0","source":{"id":"1707.04362","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.04362","created_at":"2026-05-17T23:44:10Z"},{"alias_kind":"arxiv_version","alias_value":"1707.04362v2","created_at":"2026-05-17T23:44:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.04362","created_at":"2026-05-17T23:44:10Z"},{"alias_kind":"pith_short_12","alias_value":"7AAXE7YIBBCE","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"7AAXE7YIBBCE5T27","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"7AAXE7YI","created_at":"2026-05-18T12:31:03Z"}],"graph_snapshots":[{"event_id":"sha256:e5759970d744b2cd6da0a6592c7ffb143b22ef9893b548ca8887893ad3179d30","target":"graph","created_at":"2026-05-17T23:44:10Z","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":"Phenomics is an emerging branch of modern biology that uses high throughput phenotyping tools to capture multiple environmental and phenotypic traits, often at massive spatial and temporal scales. The resulting high dimensional data represent a treasure trove of information for providing an in-depth understanding of how multiple factors interact and contribute to the overall growth and behavior of different genotypes. However, computational tools that can parse through such complex data and aid in extracting plausible hypotheses are currently lacking. In this paper, we present Hyppo-X, a new a","authors_text":"Ananth Kalyanaraman, Bala Krishnamoorthy, Methun Kamruzzaman, Patrick Schnable, Stefan Hey","cross_cats":["cs.CG","math.AT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-07-14T01:03:04Z","title":"Hyppo-X: A Scalable Exploratory Framework for Analyzing Complex Phenomics Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.04362","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":"sha256:6b4106c9d896ed7c49a8d632c2c68eece79dc0a21ddfb4b61d3a26476466093d","target":"record","created_at":"2026-05-17T23:44:10Z","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":"35a2e24f8e679daaf0c51c50b05a93a12f8e0408e7d7ad1ed98c6e61a8bdb708","cross_cats_sorted":["cs.CG","math.AT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2017-07-14T01:03:04Z","title_canon_sha256":"e56fbe48add8ca1c1e7dabb7d010d6a4cacd77ed82275acce5727431af2eb555"},"schema_version":"1.0","source":{"id":"1707.04362","kind":"arxiv","version":2}},"canonical_sha256":"f801727f0808444ecf5f41b4d00344259a38426fccf2a98cd2ab64438522f16c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f801727f0808444ecf5f41b4d00344259a38426fccf2a98cd2ab64438522f16c","first_computed_at":"2026-05-17T23:44:10.429056Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:10.429056Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sAYSdCVpF1di8c4ib8NKM9k69C+2dqv3QmweYKCYnp4PKI5yjkjlGxw95oT6x+h/c1NzhfKMuVo0GQQwzjARAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:10.429730Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.04362","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b4106c9d896ed7c49a8d632c2c68eece79dc0a21ddfb4b61d3a26476466093d","sha256:e5759970d744b2cd6da0a6592c7ffb143b22ef9893b548ca8887893ad3179d30"],"state_sha256":"cadc433c662c742055a02a8e8ed81bb080e1b9ff0d5a513fffe3d10478f216dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pIBARSstCX7+8evMJes7KN+Psi9Qj2I8gET1HdU2jpjaaAa6Mx+5FwunCX2fzsGgjsaqcjNkL/8vd+tS9KvyCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T08:33:33.062511Z","bundle_sha256":"4da8a4b66ea7afdff36d2bc2ac36ef5ca6585362a175195a16e2ccef233eeb50"}}