{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SOUP4NLD4Q3AWLG7WQ47LEH25H","short_pith_number":"pith:SOUP4NLD","canonical_record":{"source":{"id":"2405.14878","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-04-02T15:24:25Z","cross_cats_sorted":["cs.CV","cs.LG","stat.AP"],"title_canon_sha256":"ea522698e4292ffecfbb7e75813b7d48ef821c9b92d8bb05d735685f00786bd6","abstract_canon_sha256":"5d43741e709ca44b91ffadecf2c5a084d29d69abe438460a2d51f9d52db40db2"},"schema_version":"1.0"},"canonical_sha256":"93a8fe3563e4360b2cdfb439f590fae9e8ba08af689e97d30de3fc94f7d65db0","source":{"kind":"arxiv","id":"2405.14878","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.14878","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"arxiv_version","alias_value":"2405.14878v1","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.14878","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"pith_short_12","alias_value":"SOUP4NLD4Q3A","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"pith_short_16","alias_value":"SOUP4NLD4Q3AWLG7","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"pith_short_8","alias_value":"SOUP4NLD","created_at":"2026-07-05T08:22:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SOUP4NLD4Q3AWLG7WQ47LEH25H","target":"record","payload":{"canonical_record":{"source":{"id":"2405.14878","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-04-02T15:24:25Z","cross_cats_sorted":["cs.CV","cs.LG","stat.AP"],"title_canon_sha256":"ea522698e4292ffecfbb7e75813b7d48ef821c9b92d8bb05d735685f00786bd6","abstract_canon_sha256":"5d43741e709ca44b91ffadecf2c5a084d29d69abe438460a2d51f9d52db40db2"},"schema_version":"1.0"},"canonical_sha256":"93a8fe3563e4360b2cdfb439f590fae9e8ba08af689e97d30de3fc94f7d65db0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:22:42.325334Z","signature_b64":"o9CfM2X7GY0t8uTLHDYOVRvm7yTE1qIRRvoHq+ZIG8TT0A/7G1hW+agWwZmNgOGUtyAdu8FCFqXdN37nFKGxCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93a8fe3563e4360b2cdfb439f590fae9e8ba08af689e97d30de3fc94f7d65db0","last_reissued_at":"2026-07-05T08:22:42.324878Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:22:42.324878Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.14878","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":"2026-07-05T08:22:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"utZF5lBSELpIPXNaPetMHPUOrX0O0sjw2z8hbK74Ln28Vzn0F/imlYWfAmoJ7rMoOfTdgPp6rNHxOOgAeJ7uBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T05:44:52.822521Z"},"content_sha256":"88cdd9cec2d2bd06ffa8b7cef2d80445a2844e5f9d2d5d99c8e85e50afdf7bcf","schema_version":"1.0","event_id":"sha256:88cdd9cec2d2bd06ffa8b7cef2d80445a2844e5f9d2d5d99c8e85e50afdf7bcf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SOUP4NLD4Q3AWLG7WQ47LEH25H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving and Evaluating Machine Learning Methods for Forensic Shoeprint Matching","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG","stat.AP"],"primary_cat":"eess.IV","authors_text":"Anna Plantinga, Ashley Zheng, Divij Jain, Elizabeth Upton, Lena Liang, Saatvik Kher, Xizhen Cai, Yufeng Wu","submitted_at":"2024-04-02T15:24:25Z","abstract_excerpt":"We propose a machine learning pipeline for forensic shoeprint pattern matching that improves on the accuracy and generalisability of existing methods. We extract 2D coordinates from shoeprint scans using edge detection and align the two shoeprints with iterative closest point (ICP). We then extract similarity metrics to quantify how well the two prints match and use these metrics to train a random forest that generates a probabilistic measurement of how likely two prints are to have originated from the same outsole. We assess the generalisability of machine learning methods trained on lab shoe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.14878","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/2405.14878/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:22:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f/VD6Q3B7CrRwnj4EBg2FV3x+RlYFmgNudqaLAS7IE30Uol/fzOPD2wT8Jf7fY2WniPN6Av3S+z52iiZVr8pAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T05:44:52.822892Z"},"content_sha256":"607b1b18605590957081cf1ba9e94e270599746b5e412f1cf28d655f2ec54609","schema_version":"1.0","event_id":"sha256:607b1b18605590957081cf1ba9e94e270599746b5e412f1cf28d655f2ec54609"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SOUP4NLD4Q3AWLG7WQ47LEH25H/bundle.json","state_url":"https://pith.science/pith/SOUP4NLD4Q3AWLG7WQ47LEH25H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SOUP4NLD4Q3AWLG7WQ47LEH25H/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":"2026-07-06T05:44:52Z","links":{"resolver":"https://pith.science/pith/SOUP4NLD4Q3AWLG7WQ47LEH25H","bundle":"https://pith.science/pith/SOUP4NLD4Q3AWLG7WQ47LEH25H/bundle.json","state":"https://pith.science/pith/SOUP4NLD4Q3AWLG7WQ47LEH25H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SOUP4NLD4Q3AWLG7WQ47LEH25H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SOUP4NLD4Q3AWLG7WQ47LEH25H","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":"5d43741e709ca44b91ffadecf2c5a084d29d69abe438460a2d51f9d52db40db2","cross_cats_sorted":["cs.CV","cs.LG","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-04-02T15:24:25Z","title_canon_sha256":"ea522698e4292ffecfbb7e75813b7d48ef821c9b92d8bb05d735685f00786bd6"},"schema_version":"1.0","source":{"id":"2405.14878","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.14878","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"arxiv_version","alias_value":"2405.14878v1","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.14878","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"pith_short_12","alias_value":"SOUP4NLD4Q3A","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"pith_short_16","alias_value":"SOUP4NLD4Q3AWLG7","created_at":"2026-07-05T08:22:42Z"},{"alias_kind":"pith_short_8","alias_value":"SOUP4NLD","created_at":"2026-07-05T08:22:42Z"}],"graph_snapshots":[{"event_id":"sha256:607b1b18605590957081cf1ba9e94e270599746b5e412f1cf28d655f2ec54609","target":"graph","created_at":"2026-07-05T08:22:42Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2405.14878/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a machine learning pipeline for forensic shoeprint pattern matching that improves on the accuracy and generalisability of existing methods. We extract 2D coordinates from shoeprint scans using edge detection and align the two shoeprints with iterative closest point (ICP). We then extract similarity metrics to quantify how well the two prints match and use these metrics to train a random forest that generates a probabilistic measurement of how likely two prints are to have originated from the same outsole. We assess the generalisability of machine learning methods trained on lab shoe","authors_text":"Anna Plantinga, Ashley Zheng, Divij Jain, Elizabeth Upton, Lena Liang, Saatvik Kher, Xizhen Cai, Yufeng Wu","cross_cats":["cs.CV","cs.LG","stat.AP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-04-02T15:24:25Z","title":"Improving and Evaluating Machine Learning Methods for Forensic Shoeprint Matching"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.14878","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":"sha256:88cdd9cec2d2bd06ffa8b7cef2d80445a2844e5f9d2d5d99c8e85e50afdf7bcf","target":"record","created_at":"2026-07-05T08:22:42Z","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":"5d43741e709ca44b91ffadecf2c5a084d29d69abe438460a2d51f9d52db40db2","cross_cats_sorted":["cs.CV","cs.LG","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-04-02T15:24:25Z","title_canon_sha256":"ea522698e4292ffecfbb7e75813b7d48ef821c9b92d8bb05d735685f00786bd6"},"schema_version":"1.0","source":{"id":"2405.14878","kind":"arxiv","version":1}},"canonical_sha256":"93a8fe3563e4360b2cdfb439f590fae9e8ba08af689e97d30de3fc94f7d65db0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"93a8fe3563e4360b2cdfb439f590fae9e8ba08af689e97d30de3fc94f7d65db0","first_computed_at":"2026-07-05T08:22:42.324878Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:22:42.324878Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"o9CfM2X7GY0t8uTLHDYOVRvm7yTE1qIRRvoHq+ZIG8TT0A/7G1hW+agWwZmNgOGUtyAdu8FCFqXdN37nFKGxCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:22:42.325334Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.14878","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88cdd9cec2d2bd06ffa8b7cef2d80445a2844e5f9d2d5d99c8e85e50afdf7bcf","sha256:607b1b18605590957081cf1ba9e94e270599746b5e412f1cf28d655f2ec54609"],"state_sha256":"4b7da8101fcc15d8985860708b30279071dc24e2372ee7153b86ffba8d75ab02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ddsOe4r38CBq2AKnRE98iqrBBrIamGk7ACZd0kkJT2tWbdVGAUWeW60H+3Pjt96lhTlxobobhZRVEe9XRNG2BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T05:44:52.824893Z","bundle_sha256":"5d4f0675bef8da34600fa1281c788245e11bd07f90875e79199b0ebaa957959f"}}