{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HEKEJFVIBXL4ZS3FO2U2PW3WYZ","short_pith_number":"pith:HEKEJFVI","canonical_record":{"source":{"id":"1806.01933","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-05T20:40:56Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e255b1673a9694177f22673cedfaf0e9fa865ff211b585dc0bdb0527a16bd8ea","abstract_canon_sha256":"52c0290bfe5f26591076b6ebf6f53ff01abd7052dcf3de3ed349921670a4d24a"},"schema_version":"1.0"},"canonical_sha256":"39144496a80dd7cccb6576a9a7db76c6566fbdb72b59983dfe7b04c0fdfcc8eb","source":{"kind":"arxiv","id":"1806.01933","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.01933","created_at":"2026-05-18T00:14:03Z"},{"alias_kind":"arxiv_version","alias_value":"1806.01933v1","created_at":"2026-05-18T00:14:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.01933","created_at":"2026-05-18T00:14:03Z"},{"alias_kind":"pith_short_12","alias_value":"HEKEJFVIBXL4","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HEKEJFVIBXL4ZS3F","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HEKEJFVI","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HEKEJFVIBXL4ZS3FO2U2PW3WYZ","target":"record","payload":{"canonical_record":{"source":{"id":"1806.01933","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-05T20:40:56Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e255b1673a9694177f22673cedfaf0e9fa865ff211b585dc0bdb0527a16bd8ea","abstract_canon_sha256":"52c0290bfe5f26591076b6ebf6f53ff01abd7052dcf3de3ed349921670a4d24a"},"schema_version":"1.0"},"canonical_sha256":"39144496a80dd7cccb6576a9a7db76c6566fbdb72b59983dfe7b04c0fdfcc8eb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:03.400538Z","signature_b64":"Q8Ho+sriG6mkktJyfDhBN6N1WpHOAZjmqnz5Hav0X+hBSb7Ltpc5fMlmoHmqK9hfiPEU2bK31JPoupT26iMuAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"39144496a80dd7cccb6576a9a7db76c6566fbdb72b59983dfe7b04c0fdfcc8eb","last_reissued_at":"2026-05-18T00:14:03.399787Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:03.399787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.01933","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":"2026-05-18T00:14:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gay66OzLNNnyy72q48uUyg2YeCYzGQ5NXQLwCKfQrAFNR3u4JGi2Ky+qEPtd0f7lxRhrFzNIvENc99oj7snxAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T03:40:46.668101Z"},"content_sha256":"19db478e354e0eb90a9ff2eb49007ebcf501b204279deb755eaff198f3d76960","schema_version":"1.0","event_id":"sha256:19db478e354e0eb90a9ff2eb49007ebcf501b204279deb755eaff198f3d76960"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HEKEJFVIBXL4ZS3FO2U2PW3WYZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Explainable Neural Networks based on Additive Index Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Agus Sudjianto, Erind Brahimi, Jie Chen, Joel Vaughan, Vijayan N. Nair","submitted_at":"2018-06-05T20:40:56Z","abstract_excerpt":"Machine Learning algorithms are increasingly being used in recent years due to their flexibility in model fitting and increased predictive performance. However, the complexity of the models makes them hard for the data analyst to interpret the results and explain them without additional tools. This has led to much research in developing various approaches to understand the model behavior. In this paper, we present the Explainable Neural Network (xNN), a structured neural network designed especially to learn interpretable features. Unlike fully connected neural networks, the features engineered"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.01933","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":"2026-05-18T00:14:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"agJTH5aovptXwwJxa+oevTNOesAExByTKSiTnGnx9Nrxa66Mdh3Agc7PJuH4jfeIG6v3xiRQFoZZDco2m5DbCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T03:40:46.668781Z"},"content_sha256":"bb85ba9c7c24f0917d0a67432aa13b6343715ecf835c41f4cc11ae060edc102e","schema_version":"1.0","event_id":"sha256:bb85ba9c7c24f0917d0a67432aa13b6343715ecf835c41f4cc11ae060edc102e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HEKEJFVIBXL4ZS3FO2U2PW3WYZ/bundle.json","state_url":"https://pith.science/pith/HEKEJFVIBXL4ZS3FO2U2PW3WYZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HEKEJFVIBXL4ZS3FO2U2PW3WYZ/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":"2026-05-26T03:40:46Z","links":{"resolver":"https://pith.science/pith/HEKEJFVIBXL4ZS3FO2U2PW3WYZ","bundle":"https://pith.science/pith/HEKEJFVIBXL4ZS3FO2U2PW3WYZ/bundle.json","state":"https://pith.science/pith/HEKEJFVIBXL4ZS3FO2U2PW3WYZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HEKEJFVIBXL4ZS3FO2U2PW3WYZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HEKEJFVIBXL4ZS3FO2U2PW3WYZ","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":"52c0290bfe5f26591076b6ebf6f53ff01abd7052dcf3de3ed349921670a4d24a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-05T20:40:56Z","title_canon_sha256":"e255b1673a9694177f22673cedfaf0e9fa865ff211b585dc0bdb0527a16bd8ea"},"schema_version":"1.0","source":{"id":"1806.01933","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.01933","created_at":"2026-05-18T00:14:03Z"},{"alias_kind":"arxiv_version","alias_value":"1806.01933v1","created_at":"2026-05-18T00:14:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.01933","created_at":"2026-05-18T00:14:03Z"},{"alias_kind":"pith_short_12","alias_value":"HEKEJFVIBXL4","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HEKEJFVIBXL4ZS3F","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HEKEJFVI","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:bb85ba9c7c24f0917d0a67432aa13b6343715ecf835c41f4cc11ae060edc102e","target":"graph","created_at":"2026-05-18T00:14:03Z","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":"Machine Learning algorithms are increasingly being used in recent years due to their flexibility in model fitting and increased predictive performance. However, the complexity of the models makes them hard for the data analyst to interpret the results and explain them without additional tools. This has led to much research in developing various approaches to understand the model behavior. In this paper, we present the Explainable Neural Network (xNN), a structured neural network designed especially to learn interpretable features. Unlike fully connected neural networks, the features engineered","authors_text":"Agus Sudjianto, Erind Brahimi, Jie Chen, Joel Vaughan, Vijayan N. Nair","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-05T20:40:56Z","title":"Explainable Neural Networks based on Additive Index Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.01933","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":"sha256:19db478e354e0eb90a9ff2eb49007ebcf501b204279deb755eaff198f3d76960","target":"record","created_at":"2026-05-18T00:14:03Z","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":"52c0290bfe5f26591076b6ebf6f53ff01abd7052dcf3de3ed349921670a4d24a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-05T20:40:56Z","title_canon_sha256":"e255b1673a9694177f22673cedfaf0e9fa865ff211b585dc0bdb0527a16bd8ea"},"schema_version":"1.0","source":{"id":"1806.01933","kind":"arxiv","version":1}},"canonical_sha256":"39144496a80dd7cccb6576a9a7db76c6566fbdb72b59983dfe7b04c0fdfcc8eb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"39144496a80dd7cccb6576a9a7db76c6566fbdb72b59983dfe7b04c0fdfcc8eb","first_computed_at":"2026-05-18T00:14:03.399787Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:03.399787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Q8Ho+sriG6mkktJyfDhBN6N1WpHOAZjmqnz5Hav0X+hBSb7Ltpc5fMlmoHmqK9hfiPEU2bK31JPoupT26iMuAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:03.400538Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.01933","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:19db478e354e0eb90a9ff2eb49007ebcf501b204279deb755eaff198f3d76960","sha256:bb85ba9c7c24f0917d0a67432aa13b6343715ecf835c41f4cc11ae060edc102e"],"state_sha256":"a62ffa109bf5225835d7430f96f5ba471d57c6bdead589209266ac5fbccdd88d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+vyxCTp289ifIOFOfaSfaOhrg1jtOaz8w0jVyY3wx0r83w/Dp2ilPXccrOTmuF4TPTOlePCBFyFHbwLz4Z1AAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T03:40:46.672357Z","bundle_sha256":"f4c0c711406e9313ae76fa4da46f3bf69abdbe2c748d7122d3506473492f5645"}}