{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:EJHWVF7PJSEOJT3HIHOBOYACZZ","short_pith_number":"pith:EJHWVF7P","canonical_record":{"source":{"id":"2605.31007","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T08:39:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"81d065c211c43d3ac5e088a413754897d1dd449ad718b19d44a8f453d0d427dd","abstract_canon_sha256":"39b502e0dde12fcf75278127f87b539c55467a7efd46b202689a094494276e39"},"schema_version":"1.0"},"canonical_sha256":"224f6a97ef4c88e4cf6741dc176002ce4f176efe65f496ab1edb403ab05b2e01","source":{"kind":"arxiv","id":"2605.31007","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.31007","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"arxiv_version","alias_value":"2605.31007v1","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.31007","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"pith_short_12","alias_value":"EJHWVF7PJSEO","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"pith_short_16","alias_value":"EJHWVF7PJSEOJT3H","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"pith_short_8","alias_value":"EJHWVF7P","created_at":"2026-06-01T01:03:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:EJHWVF7PJSEOJT3HIHOBOYACZZ","target":"record","payload":{"canonical_record":{"source":{"id":"2605.31007","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T08:39:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"81d065c211c43d3ac5e088a413754897d1dd449ad718b19d44a8f453d0d427dd","abstract_canon_sha256":"39b502e0dde12fcf75278127f87b539c55467a7efd46b202689a094494276e39"},"schema_version":"1.0"},"canonical_sha256":"224f6a97ef4c88e4cf6741dc176002ce4f176efe65f496ab1edb403ab05b2e01","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:03:30.365785Z","signature_b64":"FkDMAHS5zxrtpTi4zkcXyhrqILjmK8HDG3VEQrbPmbVNmS0AeBtAwead7n2/XXPv68adYh5hiX6ROSCcEvbMCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"224f6a97ef4c88e4cf6741dc176002ce4f176efe65f496ab1edb403ab05b2e01","last_reissued_at":"2026-06-01T01:03:30.364929Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:03:30.364929Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.31007","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":"2026-06-01T01:03:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T3EkfKCwg3WxpeqReIjHuW9C5VifVT31ABqKI1naQwpI0dIyWTwSLSX2PrsVnVJTIZYaSoMssPewb1DtilW9Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T15:16:42.132531Z"},"content_sha256":"a2b2e8ed84b7c21560e7915f486eb34919892e1b38d0d725a235b6ba14a5f0e7","schema_version":"1.0","event_id":"sha256:a2b2e8ed84b7c21560e7915f486eb34919892e1b38d0d725a235b6ba14a5f0e7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:EJHWVF7PJSEOJT3HIHOBOYACZZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DEM: A Distilled Explanation Model for Interpretable Anomaly Detection in Physiological Sensor Networks","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Anushka Roy, Chittaranjan Hota, Jyotirmoy Singh, Shreea Bose","submitted_at":"2026-05-29T08:39:39Z","abstract_excerpt":"Anomaly detection in physiological sensor data from Wireless Body Area Networks (WBANs) can be caused by sensor faults, network disruptions, or missing data, leading to false alarms. Hence, it demands both high predictive accuracy and clinically interpretable explanations. Existing approaches rely either on black-box models that achieve strong performance but offer no transparency, or on post-prediction explanation methods such as SHAP and LIME. In this paper, we propose the Distilled Explanation Model (DEM), a three-stage glass-box framework that distills the non-linear knowledge of a gradien"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.31007","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/2605.31007/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":"2026-06-01T01:03:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YvaXbR7T7yC8wPephTzXa8pkn6GwVOfAXeI7X0bjc2cBn1sMpl4TnNNO9Gwtkizm1hYSLk33gABiPfvShrn4Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T15:16:42.132932Z"},"content_sha256":"49e82f70faf4840e773710cfc4f74e7bfe655479aa8b20ccdeffb74d5e70e5ad","schema_version":"1.0","event_id":"sha256:49e82f70faf4840e773710cfc4f74e7bfe655479aa8b20ccdeffb74d5e70e5ad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EJHWVF7PJSEOJT3HIHOBOYACZZ/bundle.json","state_url":"https://pith.science/pith/EJHWVF7PJSEOJT3HIHOBOYACZZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EJHWVF7PJSEOJT3HIHOBOYACZZ/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":"2026-06-29T15:16:42Z","links":{"resolver":"https://pith.science/pith/EJHWVF7PJSEOJT3HIHOBOYACZZ","bundle":"https://pith.science/pith/EJHWVF7PJSEOJT3HIHOBOYACZZ/bundle.json","state":"https://pith.science/pith/EJHWVF7PJSEOJT3HIHOBOYACZZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EJHWVF7PJSEOJT3HIHOBOYACZZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:EJHWVF7PJSEOJT3HIHOBOYACZZ","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":"39b502e0dde12fcf75278127f87b539c55467a7efd46b202689a094494276e39","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T08:39:39Z","title_canon_sha256":"81d065c211c43d3ac5e088a413754897d1dd449ad718b19d44a8f453d0d427dd"},"schema_version":"1.0","source":{"id":"2605.31007","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.31007","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"arxiv_version","alias_value":"2605.31007v1","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.31007","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"pith_short_12","alias_value":"EJHWVF7PJSEO","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"pith_short_16","alias_value":"EJHWVF7PJSEOJT3H","created_at":"2026-06-01T01:03:30Z"},{"alias_kind":"pith_short_8","alias_value":"EJHWVF7P","created_at":"2026-06-01T01:03:30Z"}],"graph_snapshots":[{"event_id":"sha256:49e82f70faf4840e773710cfc4f74e7bfe655479aa8b20ccdeffb74d5e70e5ad","target":"graph","created_at":"2026-06-01T01:03:30Z","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/2605.31007/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Anomaly detection in physiological sensor data from Wireless Body Area Networks (WBANs) can be caused by sensor faults, network disruptions, or missing data, leading to false alarms. Hence, it demands both high predictive accuracy and clinically interpretable explanations. Existing approaches rely either on black-box models that achieve strong performance but offer no transparency, or on post-prediction explanation methods such as SHAP and LIME. In this paper, we propose the Distilled Explanation Model (DEM), a three-stage glass-box framework that distills the non-linear knowledge of a gradien","authors_text":"Anushka Roy, Chittaranjan Hota, Jyotirmoy Singh, Shreea Bose","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T08:39:39Z","title":"DEM: A Distilled Explanation Model for Interpretable Anomaly Detection in Physiological Sensor Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.31007","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:a2b2e8ed84b7c21560e7915f486eb34919892e1b38d0d725a235b6ba14a5f0e7","target":"record","created_at":"2026-06-01T01:03:30Z","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":"39b502e0dde12fcf75278127f87b539c55467a7efd46b202689a094494276e39","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T08:39:39Z","title_canon_sha256":"81d065c211c43d3ac5e088a413754897d1dd449ad718b19d44a8f453d0d427dd"},"schema_version":"1.0","source":{"id":"2605.31007","kind":"arxiv","version":1}},"canonical_sha256":"224f6a97ef4c88e4cf6741dc176002ce4f176efe65f496ab1edb403ab05b2e01","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"224f6a97ef4c88e4cf6741dc176002ce4f176efe65f496ab1edb403ab05b2e01","first_computed_at":"2026-06-01T01:03:30.364929Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:03:30.364929Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FkDMAHS5zxrtpTi4zkcXyhrqILjmK8HDG3VEQrbPmbVNmS0AeBtAwead7n2/XXPv68adYh5hiX6ROSCcEvbMCQ==","signature_status":"signed_v1","signed_at":"2026-06-01T01:03:30.365785Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.31007","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a2b2e8ed84b7c21560e7915f486eb34919892e1b38d0d725a235b6ba14a5f0e7","sha256:49e82f70faf4840e773710cfc4f74e7bfe655479aa8b20ccdeffb74d5e70e5ad"],"state_sha256":"278baac2eaa5991facdc0647cdbbbd814089caeb41d3906d31543c7375a3fe51"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5yJ/W9S5JNTHS8c51AjwnDap/yvF33B2eNowOvs3ceCNVty2OPkYMy7+/CJJ20i3oCNTPQhsIrwaXE7T9ZhfCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T15:16:42.134897Z","bundle_sha256":"57a38a9a865c8157d4d1170f604510d8ab9fbdd0d35c050562469d2f29656817"}}