{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:V6APZ4UEJU3X5N4VTT6NCTE4DT","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":"d65bb25712a86edd52c1d70f09ff1b9345a222739f844859ea352e53615ba226","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-19T09:42:36Z","title_canon_sha256":"47b072aad39064e0ec44f645a51985ce9dacb1a97d788c8430161ad50312cbd0"},"schema_version":"1.0","source":{"id":"1806.07129","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.07129","created_at":"2026-05-18T00:12:51Z"},{"alias_kind":"arxiv_version","alias_value":"1806.07129v1","created_at":"2026-05-18T00:12:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.07129","created_at":"2026-05-18T00:12:51Z"},{"alias_kind":"pith_short_12","alias_value":"V6APZ4UEJU3X","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"V6APZ4UEJU3X5N4V","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"V6APZ4UE","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:1fc6832013395ce07d831704f75809f7d997524453da057a546daa9704a1ca34","target":"graph","created_at":"2026-05-18T00:12:51Z","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":"Fraud detection is a difficult problem that can benefit from predictive modeling. However, the verification of a prediction is challenging; for a single insurance policy, the model only provides a prediction score. We present a case study where we reflect on different instance-level model explanation techniques to aid a fraud detection team in their work. To this end, we designed two novel dashboards combining various state-of-the-art explanation techniques. These enable the domain expert to analyze and understand predictions, dramatically speeding up the process of filtering potential fraud c","authors_text":"Dennis Collaris, Jarke J. van Wijk, Leo M. Vink","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-19T09:42:36Z","title":"Instance-Level Explanations for Fraud Detection: A Case Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.07129","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":"sha256:6ff53f312a6410e0d59a9312459f237e3abb08829207e4b3a9ca416954b3a7ad","target":"record","created_at":"2026-05-18T00:12:51Z","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":"d65bb25712a86edd52c1d70f09ff1b9345a222739f844859ea352e53615ba226","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-19T09:42:36Z","title_canon_sha256":"47b072aad39064e0ec44f645a51985ce9dacb1a97d788c8430161ad50312cbd0"},"schema_version":"1.0","source":{"id":"1806.07129","kind":"arxiv","version":1}},"canonical_sha256":"af80fcf2844d377eb7959cfcd14c9c1ceeba120c64e1fc1d85a95d677e0ccedf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af80fcf2844d377eb7959cfcd14c9c1ceeba120c64e1fc1d85a95d677e0ccedf","first_computed_at":"2026-05-18T00:12:51.768601Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:12:51.768601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EwU+m92Zq6CWAucC4pnO7cTGGwpyt2jZIfBuipvM8OjXVeB9dgtjr1VQuRaZZzQ5+XNr58i1mByYtCB8cTmbCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:12:51.769133Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.07129","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6ff53f312a6410e0d59a9312459f237e3abb08829207e4b3a9ca416954b3a7ad","sha256:1fc6832013395ce07d831704f75809f7d997524453da057a546daa9704a1ca34"],"state_sha256":"f1634ca92e8a085884747a4899edde987dd2977549a6c8cca0ab17f64fe1d8d8"}