{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:XESY3XX7E3MJKBJDMBPDUA2QH4","short_pith_number":"pith:XESY3XX7","canonical_record":{"source":{"id":"1901.03896","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-12T20:23:29Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e3f06189a8d9b5fe326bedb42b1ec6d787a32aba59fffa0b8a2e5eadb0b24c0e","abstract_canon_sha256":"fcf5536e64f52a9bd5ea6ff8b0a2516e976ad4fd728a2f9a44c9f37a76d74ce9"},"schema_version":"1.0"},"canonical_sha256":"b9258ddeff26d8950523605e3a03503f2953422ce84b1deb125c668b60af4d0d","source":{"kind":"arxiv","id":"1901.03896","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.03896","created_at":"2026-05-17T23:56:26Z"},{"alias_kind":"arxiv_version","alias_value":"1901.03896v1","created_at":"2026-05-17T23:56:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.03896","created_at":"2026-05-17T23:56:26Z"},{"alias_kind":"pith_short_12","alias_value":"XESY3XX7E3MJ","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"XESY3XX7E3MJKBJD","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"XESY3XX7","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:XESY3XX7E3MJKBJDMBPDUA2QH4","target":"record","payload":{"canonical_record":{"source":{"id":"1901.03896","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-12T20:23:29Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e3f06189a8d9b5fe326bedb42b1ec6d787a32aba59fffa0b8a2e5eadb0b24c0e","abstract_canon_sha256":"fcf5536e64f52a9bd5ea6ff8b0a2516e976ad4fd728a2f9a44c9f37a76d74ce9"},"schema_version":"1.0"},"canonical_sha256":"b9258ddeff26d8950523605e3a03503f2953422ce84b1deb125c668b60af4d0d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:26.798633Z","signature_b64":"k7qYvVHM5z68nVBuTrWFKu2t8DilOodDR+9BsbqxhWQLkjPOMHJquP7QNnzuX4JFGNbRO6dneKAfRJuwu2BICw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9258ddeff26d8950523605e3a03503f2953422ce84b1deb125c668b60af4d0d","last_reissued_at":"2026-05-17T23:56:26.798133Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:26.798133Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.03896","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":"2026-05-17T23:56:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zti0XZ0FY7cGRF1RnpNLeoJ0PLTlKHzB6akD9MjWyY/jehi6cWs+qWphxZXUomq+KuKUT6Eyt4vAF//QHI4UCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T04:03:44.200183Z"},"content_sha256":"570976b43f96d1007f8bd4ed32135e35233d645c283f1ff131398dc088b58618","schema_version":"1.0","event_id":"sha256:570976b43f96d1007f8bd4ed32135e35233d645c283f1ff131398dc088b58618"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:XESY3XX7E3MJKBJDMBPDUA2QH4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Personalized Colorectal Cancer Survivability Prediction with Machine Learning Methods","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Samuel Li, Talayeh Razzaghi","submitted_at":"2019-01-12T20:23:29Z","abstract_excerpt":"In this work, we investigate the importance of ethnicity in colorectal cancer survivability prediction using machine learning techniques and the SEER cancer incidence database. We compare model performances for 2-year survivability prediction and feature importance rankings between Hispanic, White, and mixed patient populations. Our models consistently perform better on single-ethnicity populations and provide different feature importance rankings when trained in different populations. Additionally, we show our models achieve higher Area Under Curve (AUC) score than the best reported in the li"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.03896","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":"2026-05-17T23:56:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0YyTLSlZgTx5VBJm74LXbE8FRbEGcmsu4c5FbmkE6n5NTQTR1Hy+svJ2ul1X9kb6qe7xYeabaKrgPuP5IWhqAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T04:03:44.200544Z"},"content_sha256":"eaeca8375b7d341ad092bbb7bb9199e9ce50a879875f032be4d24683a72f34b5","schema_version":"1.0","event_id":"sha256:eaeca8375b7d341ad092bbb7bb9199e9ce50a879875f032be4d24683a72f34b5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XESY3XX7E3MJKBJDMBPDUA2QH4/bundle.json","state_url":"https://pith.science/pith/XESY3XX7E3MJKBJDMBPDUA2QH4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XESY3XX7E3MJKBJDMBPDUA2QH4/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":"2026-05-28T04:03:44Z","links":{"resolver":"https://pith.science/pith/XESY3XX7E3MJKBJDMBPDUA2QH4","bundle":"https://pith.science/pith/XESY3XX7E3MJKBJDMBPDUA2QH4/bundle.json","state":"https://pith.science/pith/XESY3XX7E3MJKBJDMBPDUA2QH4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XESY3XX7E3MJKBJDMBPDUA2QH4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:XESY3XX7E3MJKBJDMBPDUA2QH4","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":"fcf5536e64f52a9bd5ea6ff8b0a2516e976ad4fd728a2f9a44c9f37a76d74ce9","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-12T20:23:29Z","title_canon_sha256":"e3f06189a8d9b5fe326bedb42b1ec6d787a32aba59fffa0b8a2e5eadb0b24c0e"},"schema_version":"1.0","source":{"id":"1901.03896","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.03896","created_at":"2026-05-17T23:56:26Z"},{"alias_kind":"arxiv_version","alias_value":"1901.03896v1","created_at":"2026-05-17T23:56:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.03896","created_at":"2026-05-17T23:56:26Z"},{"alias_kind":"pith_short_12","alias_value":"XESY3XX7E3MJ","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"XESY3XX7E3MJKBJD","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"XESY3XX7","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:eaeca8375b7d341ad092bbb7bb9199e9ce50a879875f032be4d24683a72f34b5","target":"graph","created_at":"2026-05-17T23:56:26Z","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":"In this work, we investigate the importance of ethnicity in colorectal cancer survivability prediction using machine learning techniques and the SEER cancer incidence database. We compare model performances for 2-year survivability prediction and feature importance rankings between Hispanic, White, and mixed patient populations. Our models consistently perform better on single-ethnicity populations and provide different feature importance rankings when trained in different populations. Additionally, we show our models achieve higher Area Under Curve (AUC) score than the best reported in the li","authors_text":"Samuel Li, Talayeh Razzaghi","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-12T20:23:29Z","title":"Personalized Colorectal Cancer Survivability Prediction with Machine Learning Methods"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.03896","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":"sha256:570976b43f96d1007f8bd4ed32135e35233d645c283f1ff131398dc088b58618","target":"record","created_at":"2026-05-17T23:56:26Z","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":"fcf5536e64f52a9bd5ea6ff8b0a2516e976ad4fd728a2f9a44c9f37a76d74ce9","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-12T20:23:29Z","title_canon_sha256":"e3f06189a8d9b5fe326bedb42b1ec6d787a32aba59fffa0b8a2e5eadb0b24c0e"},"schema_version":"1.0","source":{"id":"1901.03896","kind":"arxiv","version":1}},"canonical_sha256":"b9258ddeff26d8950523605e3a03503f2953422ce84b1deb125c668b60af4d0d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9258ddeff26d8950523605e3a03503f2953422ce84b1deb125c668b60af4d0d","first_computed_at":"2026-05-17T23:56:26.798133Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:26.798133Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"k7qYvVHM5z68nVBuTrWFKu2t8DilOodDR+9BsbqxhWQLkjPOMHJquP7QNnzuX4JFGNbRO6dneKAfRJuwu2BICw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:26.798633Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.03896","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:570976b43f96d1007f8bd4ed32135e35233d645c283f1ff131398dc088b58618","sha256:eaeca8375b7d341ad092bbb7bb9199e9ce50a879875f032be4d24683a72f34b5"],"state_sha256":"d5afc8e77aee072366546bb25674504af1969e451fb8e8efcbff941efacd89b1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UZXaykTSGqVVsr5cdqpj5fMF2d3hcaXItHPw7eZpMkg8ra7TwiInJzl4viD1cmo9jGdC2KGzW5bUV6iFALwIDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T04:03:44.202532Z","bundle_sha256":"18828edc8800d9ca0b1578574af76203df44fdbed1767aa2005b103411e31616"}}